A collection of random thoughts and materials that might prove enlightening to me and my friends.
MathJax
Friday, April 24, 2015
Relationship between vec operator, Schur, Kronecker and Khatri-Rao product
Tuesday, March 03, 2015
Linear separability
The fraction \(F(N,d)\) of realizations that is linearly separable is given by the expression
\[ F(N,d) = \left\{
\begin{matrix}
1 \quad &\mathrm{when}\; N \le d+1 \\
\frac{1}{2^{N-1}}\sum\limits_{i=0}^d \left( \begin{matrix} N-1 \\ i \end{matrix} \right) \quad & \mathrm{when}\; N \ge d + 1
\end{matrix}\right.
\] Intuitively, the probability of separability increase with increasing dimension \(d\).
[TODO] include plot...
http://www-isl.stanford.edu/~cover/papers/paper76.pdf
Monday, March 02, 2015
Simply connectedness
A sphere (or, equivalently, a rubber ball with a hollow center) is simply connected, because any loop on the surface of a sphere can contract to a point, even though it has a "hole" in the hollow center.
The stronger condition, that the object has no holes of any dimension, is called contractibility.
- it is path-connected, and
- whenever \(p: [0,1] \rightarrow X\) and \(q: [0,1] \rightarrow X\) are two paths (i.e. continuous maps) with the same start and endpoint (\(p(0)=q(0)\) and \(p(1) == q(1)\)), then \(p\) and \(q\) are homotopic relative to {0,1}.
Examples:
- All convex sets in \(\mathbb{R}^n\) are simply connected.
- A sphere is simply connected.
Friday, February 27, 2015
Interesting courses Spring 2015
- ECE 287 Spec Topics/Comm Theory & Syst
- TuTh 5:00p-6:20p CENTR223 Franceschetti, Massimo
- MATH 287D Statistical Learning
- TuTh 5:00p-6:20p APM 5402 Bradic, Jelena
- MATH 281C Mathematical Statistics
- TuTh 2:00p-3:20p APM 5402 Arias-Castro, Ery
- MATH 280C Probability Theory
- MW 5:00p-6:20p APM 5402 Williams, Ruth J
- MATH 245C Convex Analysis and Optimization III
- MWF 4:00p-4:50p APM 5402 Nie, Jiawang
- MATH 140C Foundations of Real Analysis III
- MWF 1:00p-1:50p HSS 1128A Saab, Rayan
- CSE 255 Data Mining and Predictive Analytics
- TuTh 3:30p-4:50p WLH 2207 Freund, Yoav
- CSE 291 Neural Networks
- TuTh 2:00p-3:20p WLH 2113 Cottrell, Garrison W
- CSE 272 Advanced Image Synthesis
- TuTh 11:00a-12:20p EBU3B 4140 Jensen, Henrik
Tuesday, February 24, 2015
Epigraph
Saturday, February 14, 2015
Entropy maximization, part II
We define the expectation
\[\sum_i \alpha_i p_i = \beta \] The optimization problem is given as
\[\max_\mathbf{p} H(\mathbf{p}) \; s.t., \; \sum_i p_i = 1,\; \sum_i \alpha_i p_i = \beta\] Optimizing using Lagrange multipliers \(\lambda\) and \(\mu\), we have
\[ p_i = exp^{-(1-\lambda)}exp^{\mu \alpha_i}\] which turns out to be the familiar expression
\[p_i = \frac{1}{Z}exp^{\mu \alpha_i}\] with \(Z=\sum_i exp^{\mu \alpha_i}\) being the partition function.
The above form is called a Gibbs distribution.
Now consider the problem where with \(\mathcal{X} \in \mathbb{R}^p\) and we are given the moments \(E[f_j(\mathcal{X})]=\beta_j, j=1,\dots,p\). The optimization problem becomes
\[\max_\mathbf{p} H(\mathbf{p}) \; s.t., \; \sum_i p_i = 1,\; \sum_i \alpha_{ij} p_i = \beta_j\] The expression have the form
\[p_i = \frac{1}{Z} exp^{\sum_{j=1}^p \mu_j \alpha_{ij}}
=\frac{1}{Z} exp^{\mathbf{\mu}^T \mathbf{\alpha_{i}}}\] Since the distribution in general has infinite support the constraint on the moment will allow one to reach a unique solution.
Friday, February 13, 2015
Entropy maximization
The Laplace's principle of insufficient reasoning, calls for assuming uniformity unless there is additional information.
Entropy maximization is the equivalent of minimizing the KL-Divergence between the distribution \(p\) and the uniform distribution.
More precisely, let \(\mathcal{X} \in \{\alpha_1, \cdots, \alpha_n\}\) be a random variable with finite alphabet, given a family of distribution \(\mathcal{P}\) and the uniform distribution \(u\),
\[ \underset{p\in\mathcal{P}}{\text{arg min}} \;D_{KL}(p\| u) = \underset{p\in\mathcal{P}}{\text{arg max}} \;H(p)\] where \(H(p)\) is the entropy.
Proof:
\[ D(p\|u) = \sum_i p_i \log p_i + (\sum_i p_i) \log (n) = \log (n) - H(p) \]
Thursday, February 12, 2015
A Side Path to Statistical Mechanics
- States of low energy have a higher probability of occurrence than states of high energy.
- As the temperature \(T\) is reduced, the probability is concentrated on a smaller subset of low-energy states.
The Helmholtz free energy of a physical system, denoted by \(F\), is defined in terms of the partition function \(Z\) as follows
\[F = -T \log Z.\] The average energy of the system is defined by
\[\lt E\gt = \sum_i p_i E_i\] The difference between the average energy and free energy is
\[\lt E \gt - F = -T\sum_i p_i \log p_i\] which we can rewrite in terms of entropy \(H\)
\[\lt E \gt - F = T H\] or, equivalently,
\[F = \lt E \gt - TH\]. The entropy of any systems tend to increase until it reaches an equilibrium, and therefore the free energy of the system will reach a minimum.
This is an important principle called the principle of minimal free energy.
Cross Entropy
\[H(p,q)=E_p[-\log q]\] It can be viewed as
\[H(p,q)=H(p)+D_{KL}(p\|q)\] where \(H(p)\) is the entropy of \(p\) and \(D_{KL}(p\|q)\) is the non-negative Kullback–Leibler divergence.
From an source coding perspective, it is the total bits required to encode information if the estimated distributed \(q\) diverged from the true distribution \(p\), where \(H(p)\) is the minimum.
This quantity is very useful in machine learning. Viewed from a vector quantization point of view, logistic regression is a way of finding an optimal boundary to classifying samples in a (possibly high dimensional) space of interest. This expression quantifies the loss of estimating distribution \(q\) instead of the true distribution \(p\). Since \(H(p)\) is fixed because it is a property of the underlying true distribution, minimizing cross-entropy is equivalent to minimizing KL divergence in this setting.
Friday, January 30, 2015
Conditional Expectation
Theorem 2 Radon-Nikodym Theorem Let \((\Omega,\mathcal{B},P)\) be the probability space. Suppose \(v\) is a positive bounded measure and \(v \ll P\). Then there exists an integrable random variable \(X\in \mathcal{B}\), such that
\[v(E) = \int_E XdP, \quad \forall E \in \mathcal{B} \] \(X\) is a.s. unique (\(P\)) and is written
\[X=\frac{dv}{dP}.\] We also write \(dv=XdP\)
Definition of Conditional Expectation
Suppose \(X\in L_1(\Omega,\mathcal{B},P)\) and let \(\mathcal{G}\subset \mathcal{B}\) be a sub-\(\sigma\)-field. Then there exists a random variable \(E(X|\mathcal{G})\), called the conditional expectation of \(X\) with respect to \(\mathcal{G}\), such that
- \(E(X|\mathcal{G})\) is \(\mathcal{G}\)-measurable and integrable.
- For all \(G\in\mathcal{G}\) we have \[ \int_G XdP = \int_G E(X|\mathcal{G})dP\]
- Definition of conditional probability: Given \((\Omega,\mathcal{B},P)\), a probability space, with \(\mathcal{G}\) a sub-\(\sigma\)-field of \(\mathcal{B}\), define \[P(A|\mathcal{G})=E(1_A|\mathcal{G}), \quad A\in \mathcal{B}.\] Thus \(P(A|\mathcal{G}) \) is a random variable such that
- \(P(A|\mathcal{G}) \) is \(\mathcal{G}\)-measurable and integrable.
- \(P(A|\mathcal{G}) \) satisfies \[\int_G P(A|\mathcal{G})dP = P(A\cap G), \quad \forall G \in \mathcal{G}. \]
- Conditioning on random variables: Suppose \(\{X_t, t\in T \}\) is a family of random variables defined on \((\Omega,\mathcal{B})\) and indexed by some index set \(T\). Define \[\mathcal{G}:=\sigma(X_t,t\in T)\] to be the \sigma-field generated by the process \(\{X_t, t\in T \}\). Then define \[E(X|X_t, t\in T)= E(X|\mathcal{G}).\]
Countable partitions Let \(\{\Lambda_n, n\ge 1 \}\) be a partition of \(\Omega\) so thyat \(\Lambda_i \cap \Lambda_j = \emptyset, i\neq j\), and \(\sum_n \Lambda_n=\Omega\). Define
\[\mathcal{G}=\sigma(\Lambda_n, n\ge 1)\] so that
\[\mathcal{G}=\left\{ \sum_{i\in J}\Lambda_i: J\subset\{1,2,\dots \} \right\}.\] For \(X\in L_1(P)\), define
\[E_{\Lambda_n}(X)=\int XP(d\omega|\Lambda_n)=\int_{\Lambda_n}XdP/P\Lambda_n , \] if \(P(\Lambda_n)>0\) and \(E_{\Lambda_n}(X) = 18\) if \(P(\Lambda_n)=0\). We claim
- \[E(X|\mathcal{G})\overset{a.s.}{=} \sum_{n=1}^\infty E_{\Lambda_n}(X) 1_{\Lambda_n} \] and for any \(A\in \mathcal{B}\)
- \[P(A|\mathcal{G})\overset{a.s.}{=} \sum_{n=1}^\infty P(A|\Lambda_n)1_{\Lambda_n}\]
Product Spaces, Transition Kernel and Rubini's Theorem
\[A_{w_1}\in \mathcal{B_2}\]
Corollary 1. Sections of measurable functions are measurable. That is if
\[ X: (\Omega_1\times \Omega_2, \mathcal{B}_1 \times \mathcal{B}_2) \mapsto (S,\mathcal{S})\] then \[ X_{\omega_1} \in \mathcal{B}_2. \] We say \(X_{\omega_1}\) is \(\mathcal{B}/\mathcal{S}\) measurable.
Define the transition (probability) kernel
- for each \(\omega_1, K(\omega_1,\cdot)\) is a probability measure on \(\mathcal{B}_2\), and
- for each \(A_2\in \mathcal{B}_2, K(\cdot, A_2)\) is \(\mathcal{B}_1/\mathcal{B}([0,1])\) measurable.
Theorem 2. Marginalization Let \(P_1\) be a probability measure on \((\Omega_1,\mathcal{B}_1)\) and suppose \(K: \Omega_1\times \mathcal{B_2} \mapsto [0,1]\) is a transition kernel. Define \(P\) on \((\Omega_1 \times \Omega_2, \mathcal{B_1}\times \mathcal{B_2})\) by
\[P(A_1\times A_2)= \int_{A_1} K(\omega_1,A_2)P_1(d\omega_1). \] Assume
\[X:(\Omega_1\times \Omega_2, \mathcal{B}_1\times \mathcal{B}_2) \mapsto (\mathbb{R},\mathcal{B}(\mathbb{R})) \] and furthermore suppose \(X\) is integrable. Then
\[Y(\omega_1)=\int_{\Omega_2} K(\omega_1,d\omega_2)X_{\omega_2}(\omega_2)\] has the properties
- \(Y\) is well defined.
- \(Y \in B_1\)
- \(Y \in L_1(P_1)\) and furthermore
\int_{\Omega_1\times \Omega_2}XdP &= \int_{\Omega_1}[ \int_{\Omega_2}X_{\omega_1}(\omega_2) P_2(d\omega_2) ] P_1(d\omega_1) \\
&= \int_{\Omega_2}[ \int_{\Omega_1}X_{\omega_2}(\omega_1) P_1(d\omega_1) ] P_2(d\omega_2)
\end{aligned} \]
Thursday, January 29, 2015
Clarification of Expectation
\[F := P \circ X^{-1}\] on \((\mathbb{R},\mathcal{B}(\mathbb{R}))\) defined by
\[F(A)=P\circ X^{-1}(A) = P[X\in A].\]
The distribution function of \(X\) is
\[F(x):= F((-\infty,x])=P[X\leq x].\] Note that the letter "F" is overloaded in two ways.
An application of the Transformation Theorem allows us to compute the abstract integral
\[E(X) = \int_\Omega XdP\] as
\[E(X) = \int_\mathbb{R} xF(dx),\] which is an integral on \(\mathbb{R}\).
More precisely,
\[E(X) = \int_\Omega X(\omega)P(d\omega)=\int_\mathbb{R} x F(dx).\]
Also given a measurable function \(g(X)\), The expectation of \(g(X)\) is
\[E(g(X)) = \int_\Omega g(X(\omega))P(d\omega)=\int_\mathbb{R} g(x) F(dx).\]
Instead of computing expectations on the abstract space \(\Omega\), one can always compute them on \(\mathbb{R}\) using \(F\), the distribution of \(X\).
Random variables and Inverse maps
Suppose \(\Omega\) and \(\Omega'\) are two sets. Often \(\Omega' = \mathbb{R}\). Suppose
\[X:\Omega \mapsto \Omega',\] Then \(X\) determines an inverse map (a set valued function)
\[X^{-1}: \mathcal{P}(\Omega')\mapsto \mathcal{P}(\Omega)\] defined by
\[X^{-1}(A') = \{\omega \in \Omega : X(\omega) \in A'\}\] for \(A' \subset \Omega'\).
\(X^{-1}\) preserves complementation, union and intersections.
Wednesday, January 28, 2015
Convergence Concepts
1. Almost Sure Convergence
Examples of statements that hold almost surely (a.s.)
- Let \(X,X'\) be two random variables. Then \(X=X'\) a.s. means \[P[X=X']=1;\] that is, there exists an event \(N\in \mathcal{B}\), such that \(P(N)=0\) and if \(\omega\in N^c\), then \(X(\omega)=X'(\omega)\).
- If \(\{X_n\}\) is a sequence of random variables, then \(\lim_{n\rightarrow \infty}X_n\) exists a.s. means there exists an event \(N\in \mathcal{B}\), such that \(P(N)=0\) and if \(\omega\in N^c\) then \[\lim_{n\rightarrow \infty}X_n(w)\] exists. It also means that for a.a. \(\omega\), \[\underset{n\rightarrow \infty}{\text{lim sup}}X_n(\omega)=\underset{n\rightarrow \infty}{\text{lim inf}}X_n(\omega).\] We will write \(\lim_{n\rightarrow \infty}X_n = X\) or \(X_n \overset{a.s.}{\rightarrow}X\).
- If \(\{X_n\}\) is a sequence of random variables, then \(\sum_n X_n\) converges a.s. means there exists an event \(N\in \mathcal{B}\), such that \(P(N)=0\), and \(\omega \in N^c\) implies \(\sum_n X_n(w)\) converges.
2. Convergence in Probability
Suppose \(X_n, n\ge 1\) and \(X\) are random variables. Then \({X_n}\) converges in probability (i.p.) to \(X\), written \(X_n \overset{P}{\rightarrow}X\), if for any \(\epsilon > 0\) \[ \lim_{n\rightarrow \infty} P[|X_n-X|>\epsilon]=0.\]
Almost sure convergence of \(\{X_n\}\) demands that for a.e. \(\omega\), \(X_n(w)-X(w)\) gets small and stay small. Convergence i.p. is weaker and merely requires that the probability of the difference \(X_n(w)-X(w)\) being non-trivial become small.
It is possible for a sequence to converge in probability but not almost surely.
Theorem 1. Convergence a.s. implies convergence i.p. Suppose that \(X_n, n\ge 1\) and \(X\) are random variables on a probability space \((\Omega,\mathcal{B},P)\). If \[ X_n \rightarrow X, \; a.s.\] then \[X_n \overset{P}{\rightarrow}X.\]
Proof. If \(X_n \rightarrow X\) a.s. then for any \(\epsilon\),
\[\begin{aligned}
0\;&=P([|X_n-X|>\epsilon]i.o.) \\
&=P(\underset{n\rightarrow \infty}{\text{lim sup}}[|X_n-X|>\epsilon]) \\
&=\lim_{N\rightarrow \infty}P(\bigcup_{n\ge N}[|X_n-X|>\epsilon] ) \\
&\ge \lim_{n\rightarrow \infty}P[|X_n-X|>\epsilon]
\end{aligned} \]
3. \(L_p\) Convergence
Recall the notation \(X\in L_p\) which means \(E(|X|^p)<\infty \). For random variables \(X,Y\in L_p\), we define the \(L_p\) metric for \(p\ge 1\) by
\[d(X,Y)=(E|X-Y|^p)^{1/p}.\] This metric is norm induced because
\[\|X\|_p := (E|X|^p)^{1/p} \] is a norm on the space \(L_p\).
A sequence \(\{X_n\}\) of random variables converges in \(L_p\) to \(X\), written
\[X_n \overset{L_p}{\rightarrow}X , \] if
\[ E(|X_n-X|^p) \rightarrow 0 \] as \(n\rightarrow \infty\).
Facts about \(L_p\) convergence.
- \(L_p\) convergence implies convergence in probability: For \(p>0\), if \(X_n\overset{L_p}{\rightarrow} X\) then \(X_n \overset{P}{\rightarrow}X \). This follows readily from Chebychev's inequality, \[P[|X_n-X|\ge \epsilon] \leq \frac{E(|X_n-X|^p|)}{\epsilon^p} \rightarrow 0.\]
- Convergence in probability does not imply \(L_p\) convergence. What can go wrong is that the \(n\)th function in the sequence can be huge on a very small set.
Example. Let the probability space be \( ([0,1],\mathcal{B}([0,1]),\lambda) \), where \(\lambda\) is Lebesgue measure and define
\[X_n = 2^n 1_{(0,\frac{1}{n}) }\] then
\[P[|X_n| > \epsilon ] = P \left( (0,\frac{1}{n}) \right) = \frac{1}{n} \rightarrow 0 \] but
\[ E(|X_n|^p) = 2^{np} \frac{1}{n} \rightarrow \infty \] - \(L_p\) convergence does not imply almost sure convergence.
Example. Consider the functions \(\{X_n\}\) defined on \( ([0,1],\mathcal{B}([0,1]),\lambda) \), where \(\lambda\) is Lebesgue measure.
\begin{align*}
X_1 &= 1_{[0,\frac{1}{2}]}, \quad X_2 = 1_{[\frac{1}{2},1]} \\
X_3 &= 1_{[0,\frac{1}{3}]}, \quad X_4 = 1_{[\frac{1}{3},\frac{2}{3}]} \\
X_5 &= 1_{[\frac{1}{3},1]}, \quad X_6 = 1_{[0,\frac{1}{4}]}, \cdots \\
\end{align*} and so on, Note that for any \(p>0\),
\[ E(|X_1|^p)=E(|X_2|^p)=\frac{1}{2},\\
E(|X_3|^p)=E(|X_4|^p)=E(|X_5|^p)=\frac{1}{3}, \\
E(|X_6|^p)=\frac{1}{4}, \cdots \] so \(E(|X_n|^p) \rightarrow 0\) and
\[X_n \xrightarrow[]{L_p} 0.\]
Observe that \(\{X_n\}\) does not converge almost surely to 0.
Limits and Integrals
Theorem 1. Monotone Convergence Theorem (MCT). If
\[0\leq X_n \uparrow X\]then
\[0\leq E(X_n) \uparrow E(X)\]
Corollary 1. Series Version of MCT. If \(X_n \ge 0\) are non-negative random variables for \(n\ge1\), then
\[E(\sum_{n=1}^\infty X_n)= \sum_{n=1}^\infty E(X_n)\]
so that the expectation and infinite sum can be interchanged
Theorem 2. Fatou Lemma. If \(X_n \ge 0\), then
\[ E(\underset{n\rightarrow \infty}{\text{lim inf}} X_n ) \leq \underset{n\rightarrow \infty}{\text{lim inf}}E(X_n)\]
More generally, if there exists \(Z\in L_1\) and \(X_n\ge Z\), then
\[ E(\underset{n\rightarrow \infty}{\text{lim inf}} X_n ) \leq \underset{n\rightarrow \infty}{\text{lim inf}}E(X_n)\]
Corollary 2. More Fatou. If \( 0 \leq X_n \leq Z\) where \(Z\in L_1\), then
\[ E(\underset{n\rightarrow \infty}{\text{lim sup}} X_n ) \ge \underset{n\rightarrow \infty}{\text{lim sup}}E(X_n)\]
Theorem 3. Dominated Convergence Theorem (DCT). If
\[X_n \rightarrow X\] and there exists a dominating random variable \(Z\in L_1\) such that
\[ |X_n| \leq Z\]then
\[E(X_n)\rightarrow E(X) \; \text{and} \; E|X_n-X|\rightarrow 0.\]
\(
\newcommand{\scriptB}{\mathcal{B}}
\newcommand{\scriptP}{\mathcal{P}}
\newcommand{\vecX}{\mathbf{X}}
\newcommand{\vecx}{\mathbf{x}}
\newcommand{\reals}{\mathbb{R}}
\newcommand{\cplxs}{\mathbb{C}}
\newcommand{\rationals}{\mathbb{Q}}
\newcommand{\naturals}{\mathbb{N}}
\newcommand{\integers}{\mathbb{Z}}
\newcommand{\ntoinf}{n\rightarrow\infty}
\newcommand{\mtoinf}{m\rightarrow\infty}
\newcommand{\tendsto}{\rightarrow}
\)
Example of when interchanging limits and integrals without the dominating condition. (When something very nasty happens on a small set and the degree of nastiness overpowers the degree of smallness).
Let
\[ (\Omega, \scriptB, P) = ([0,1], \scriptB([0,1]), \lambda)\] \(\lambda\) the Lebesgue measure. Define
\[ X_n = n^2 1_{(0,1/n)}. \] For any \(\omega \in [0,1]\),
\[ 1_{(0,1/n)}(w) \tendsto 0,\] so
\[ X_n \tendsto 0. \] However
\[ E(X_n) = n^2 \cdot \frac{1}{n} = n \tendsto \infty, \] so
\[ E(\liminf_{\ntoinf} X_n) = 0 \le \liminf_{\ntoinf} (EX_n) = \infty \] and
\[ E(\limsup_{\ntoinf} X_n) = 0 \not\ge \limsup_{\ntoinf} (EX_n) = \infty.\]
Tuesday, January 27, 2015
Zero-One Laws
Proposition 1. Borel-Cantelli Lemma Let \(\{A_n\}\) be any events (not necessarily independent).
If \(\sum_n{P(A_n)}<\infty\), then
\[P([A_n \; i.o.])=P(\underset{n\rightarrow \infty}{\text{lim sup}} A_n) = 0\].
Proposition 2. Borel Zero-One Law If \(\{A_n\}\) is a sequence of independent events, then
\[ \begin{equation*}
P([A_n \; i.o.])= \begin{cases}
0, \quad & \text{iff} \sum_n P(A_n) < \infty \\
1, \quad & \text{iff} \sum_n P(A_n) = \infty
\end{cases}
\end{equation*}
\]
Definition. An almost trivial \(\sigma\)-field is a \(\sigma\)-field all of whose events has probability 0 or 1.
Theorem 3. Kolmogorov Zero-One Law If \(\{X_n\}\) are independent random variables with tail \(\sigma\)-field \(\mathcal{T}\), then \(\Lambda\in \mathcal{T}\) implies \(P(\Lambda)=0\) or 1 so that the tail \(\sigma\)-field is almost trivial.
Lemma 4. Almost trivial \(\sigma\)-fields Let \(\mathcal{G}\) be an almost trivial \(\sigma\)-field and let \(X\) be a random variable measurable with respect to \(\mathcal{G}\). Then there exists \(c\) such that \(P[X=c] = 1\).
Corollary 5. Let \(\{X_n\}\) be independent random variables. Then the following are true.
(a) The event
\[ [\sum_n X_n \;converges] \] has probability 0 or 1.
(b) The random variables \(\text{lim sup}_{n\rightarrow \infty}X_n\) and \(\text{lim inf}_{n\rightarrow \infty}X_n\) are constant with probability 1.
(c) The event
\[ \{\omega: S_n(\omega)/n \rightarrow 0 \} \] has probability 0 or 1.
Monday, January 26, 2015
Inequalities
Friday, January 23, 2015
Dynkin's theorem
A class of subsets \(\mathcal{L}\) of \(\Omega\) is called a \(\lambda\)-system if it satisfies the following postulates
1. \(\Omega\in \mathcal{L}\)
2. \(A\in\mathcal{L} \Rightarrow A^c \in \mathcal{L}\)
3. \(n\neq m, A_nA_m = \emptyset, A_n \in \mathcal{L} \Rightarrow \cup_n A_n \in \mathcal{L}\)
It is clear that a \(\sigma\)-field is always a \(\lambda\)-system.
Next a \(\pi\)-system is a class of sets closed under finite intersections.
Dynkin's theorem
a) if \(\mathcal{P}\) is a \(\pi\)-system and \(\mathcal{L}\) is a \(\lambda\)-system such that \(\mathcal{P}\subset\mathcal{L}\), then \(\sigma(\mathcal{P})\subset \mathcal{L}\).
b) If \(\mathcal{P}\) is a \(\pi\)-system,
\(\sigma(\mathcal{P})=\mathcal{L}(\mathcal{P})\)
that is, the minimal \(\sigma\)-field over \(\mathcal{P}\) equals the minimal \(\lambda\)-system over \(\mathcal{P}\)
Wednesday, January 21, 2015
An example of Stein's paradox
Given a sample of \(N\) measurements of \(X\sim\mathcal{N}(\mu,\sigma I_p)\) with unknown parameter vector \(\mu\) of length \(p\).
\hat{\mu}_{JS}=\left (1-\frac{(p-2)\frac{\sigma^2}{N}}{\|\bar{x} \|^2}\right ) \bar{x}
\end{equation*}
where \(\bar{x}\) is the sample mean.
This estimator dominates the MLE everywhere in terms of MSE. For all \(\mu\in\mathbb{R}^p\),
\begin{equation*}
\mathbb{E}_\mu \| \hat{\mu}_{JS}-\mu\|^2 < \mathbb{E}_\mu \| \hat{\mu}_{MLE}-\mu\|^2
\end{equation*}
This makes the MLE inadmissible for \(p\ge3\)!
Wednesday, January 14, 2015
The need for measure theory
Such pathological sets almost never come up in practical applications of mathematics. Because of this, the standard solution to the problem of measure has been to abandon the goal of measuring every subset \(E\) of \(\mathbb{R}^d\) and instead to settle for only measuring a certain subclass of
non-pathological subsets of \(\mathbb{R}^d\), referred to as the measurable sets.
The most fundamental concepts of measure is the properties of
- finite or countable additivity
- translation invariance
- rotation invariance
Probability space concepts
From de Morgan's laws a field is also closed under finite intersection.
A \(\sigma\)-field \(\mathcal{B}\) is a non-empty class of subsets of \(\Omega\) closed under countable union, countable intersection and complements. A synonym for \(\sigma\)-field is \(\sigma\)-algebra.
In probability theory, the event space is a \(\sigma\)-field. This allows us enough flexibility constructing new-events from old ones (closure) but not so much flexibility that we have trouble assigning probabilities to the elements of the \(\sigma\)-field.
For the Reals, we start with sets that we know how to assign probabilities.
Supposes \(\Omega=\mathbb{R}\) and let
\(\mathcal{C}=\{(a,b],-\infty \leq a \leq b < \infty \}\)
The Borel sets is defined as
\(\mathcal{B}(\mathbb{R}) \equiv \sigma(\mathcal{C})\)
Also one can show that
\(\mathcal{B}(\mathbb{R}) = \sigma(\text{open sets in } \mathbb{R}) \)
Wednesday, January 07, 2015
Russell's Paradox
Tuesday, December 30, 2014
Message passing on codes with cycles
- Except for some degenerate cases, message passing in the presence of cycles is strictly suboptimal.
- For codes with cycles, message passing no longer performs MAP decoding.
Monday, December 22, 2014
Interesting courses Winter 2015
- ECE 275A Parameter Estimation II
- TuTh 5:00p-6:20p York 4050A Kreutz-Delgado, Kenneth
- ECE 285 Sparsity and Compressed Sensing
- MW 5:00p-6:20p WLH 2110 Rao, B
- ECE 259C Advanced Topics in Coding
- TuTh 5:00p-6:20p HSS 2305B Siegel, Paul
- CSE 250B Learning Algorithms
- TuTh 3:30p-4:50p CENTR 105 Dasgupta, Sanjoy
- MATH 245B Convex Analysis
- MWF 4:00p-4:50p APM 7421 Nie, Jiawang
- MATH 251B Lie Groups
- MWF 1:00p-1:50p APM B412 Kemp, Todd
- MATH 282B Applied Statistics II
- TuTh 11:30a-12:50p APM 5402 Arias-Castro, Ery
- MATH 280B Probability Theory
- MW 5:00p-6:20p APM 5402 Williams, Ruth J
Wednesday, December 03, 2014
Application of matrix congruence and similarity
If \(\Sigma_1 \leq \Sigma_2\), then \(\Sigma_1^{-1} \ge \Sigma_2^{-1}\)
Note that by assumption \(B=\Sigma_2 - \Sigma_1\) is positive semi-definite. If I can show that the resolvent identity of \(\Sigma_1^{-1} - \Sigma_2^{-1}\), \(\Sigma_2^{-1} (\Sigma_2 - \Sigma_1 ) \Sigma_1^{-1}\) is positive semi-definite, then the above statement is verified.
This requires the following two results:
Sylvester's Law of Inertia
Symmetric matrices \(A\) and \(B\) are congruent (i.e. there is a non-singular matrix \(C\) such that \(C^TAC=B\)) if and only if \(A\) and \(B\) have the same inertia. They have the same number of positive, negative and zero eigenvalues.Theorem 1.
The product of a symmetric positive definite matrix \(A\) and a symmetric matrix \(B\) has the same inertia as \(B\)Proof
Note that \(A^{-1/2}ABA^{1/2} = A^{1/2}BA^{1/2}\). The right hand side is similar to \(AB\), which means they have the same eigenvalues. Since \(A^{1/2}\) is symmetric, the matrix \(A^{1/2}BA^{1/2}\) is congruent to \(B\). By Sylvester's Law of inertia, the eignevalues of \(B\) have the same inertia as \(A^{1/2}BA^{1/2}\) and also of \(AB\).
The main point from Theorem 1 is that multiplying a positive definite matrix \(A\) to any symmetric matrix \(B\) will not change the inertia of the result. Note that \(\Sigma_2^{-1}\) and \(\Sigma_1^{-1}\) are positive definite. We let \(\Sigma_2^{-1}= A_1\), \(\Sigma_1^{-1}=A_2\) and \(\Sigma_2-\Sigma_1 =B\), and applying Theorem 1 twice, leads to \(\Sigma_2^{-1} (\Sigma_2 - \Sigma_1 ) \Sigma_1^{-1}\) positive semi-definite. We have shown \(\Sigma_1^{-1} - \Sigma_2^{-1}\) is indeed positive semi-definite.
Caution!
For real positive definite matrices, not all of them are symmetric! For example, given a symmetric positive definite matrix \(B\) and a anti-symmetric matrix \(C\) (\(C^T=-C\)), the sum of which (\(A=B+C\)) is positive definite. Extra care must be taken. All references of positive definiteness are within the context of symmetric matrices.
Friday, November 07, 2014
Mathematical structure of quantum mechanics
- A quantum description consists of a Hilbert space of states
- Observables are self adjoint operators on the space of states
- Time evolution is given by a one-parameter group of unitary transformations on the Hilbert space of states
- Physical symmetries are realized by unitary transformations
Postulates of quantum mechanics
Tensor Calculus
- vector (contra-variant vector) - arrow in space
- covector (co-variant vector) - gradient
Monday, November 03, 2014
Eigenvalues and Eigenvectors
- \(\lambda\in \lambda(A) \Leftrightarrow A-\lambda I \text{ is singular} \Leftrightarrow \text{det}(A-\lambda I)=0\)
- \(\{x\neq0|x\in \mathcal{N}(A-\lambda I)\}\) is the set of all eigenvectors associated with \(\lambda\).
- \(\mathcal{N}(A-\lambda I)\) is the eigenspace for A.
Diagonalizability of a matrix
- A nilpotent matrix \(A=\{A\in M_n |A^2=0\}\) is not diagonalizable.
- Two matrices \(A\) and \(B\) are similar whenever these exists a nonsingular matrix \(P\) such that \(P^{-1} AP=B\)
- A matrix can be diagonalized if it is similar to a diagonal matrix \(D\), i.e. \(P^{-1}AP=D\)
- Or equivalently, \(AP_{*,j}=\lambda_j P_{*,j}\)
- \(A\) is diagonalizable if and only if \(A\) possesses a complete set of eigenvectors.
- Or equivalently, the geometric multiplicity of \(\lambda_i\) is equal to the algebraic multiplicity of \(\lambda_i\) for each \(\lambda_i\in \lambda(A)\)
Saturday, October 11, 2014
Orthogonality Principle for LS solution
Geometric condition for a Minimum Norm LS Solution: \(x\in\mathcal{N}(A)^\perp\)
Notes on interesting mathematical objects
- A complete linear vector space
- A complete inner product space (also a Banach space)
- Well defined concept of orthogonality or angle
- Norm induced by the associated inner product
Closed set
- contains all its limit points
- complement of an open set
- every Cauchy sequence of points in M has a limit in M
- there are no points missing (inside or at the boundary)
Monday, October 06, 2014
Personalities in RMT
- Roman Vershynin, UMich
- http://www-personal.umich.edu/~romanv/
- Mark Rudelson, U of Missouri
- http://www.math.missouri.edu/~rudelson/
- Mérouane Debbah, Supelec, France
- http://www.flexible-radio.com/merouane-debbah
- Romain Couillet, Supelec, France
- http://couillet.romain.perso.sfr.fr/
Friday, September 05, 2014
On control and analysis of dynamical systems
- Even when simple feed-forward control of a linear, time invariant, first order plant was involved, the analysis of the resulting closed-loop dynamics could be involved - the equations becomes linear, time-varying equations.
- Once feedback control is involved, the equations become nonlinear and time varying.
Thursday, August 21, 2014
Interesting courses for fall 2014
- ECON 109 Game Theory
- MWF 12:00p-12:50p PCYNH 109 Newhouse, Herbert S
- MAE 281A/B Nonlinear Systems and Control (Prof. Krstic/Cortes)
- ... Not offered
- ECE 271A Statistical Learning I
- TuTh 12:30p-1:50p WLH 2205 Vasconcelos, Nuno
- ECE 275A Parameter Estimation I
- TuTh 2:00p-3:20p PETER 104 Kreutz-Delgado, Kenneth
- ECE 251C Filter Banks and Wavelets
- TuTh 3:30p-4:50p WLH 2110 Rao, B
- ECE 293 Comm. Theory Seminar
- W 3:00p-3:50p EBU1 4309 Kim, Young-Han
- CSE 250 Probabilistic Learning
- TuTh 12:30p-1:50p HSS 1330 Saul, Lawrence
- MATH 245A Convex Analysis
- MWF 4:00p-4:50p APM 5829 Nie, Jiawang
- MATH 271A/B/C Numerical Optimization (Philip E. Gill)
- ... Not offered
- MATH 280A Probability Theory
- MW 5:00p-6:20p APM 6402 Williams, Ruth J
- MATH 286 Stochastic Differential Equations
- MWF 4:00p-4:50p APM B412 Schweinsberg, Jason
Wednesday, August 20, 2014
Notes on Clang
- Clang and LLVM disable RTTI. As such the object files do not contain RTTI information.
- ensure the -fno-rtti flag is set
Good questions on C
- Difference between external linkage and internal linkage
- default linkage for non-const and const in C
- use of extern and static keyword
- Use of unnamed namespace in C++ vs static keyword
Tuesday, August 19, 2014
Building Clang (cont.)
Perform a Release (Optimized) build.
Perform a Release (Optimized) build without assertions enabled.
Perform a Debug build.
Perform a Profiling build.
Print what gmake is doing on standard output.
Ask each tool invoked by the makefiles to print out what it is doing on the standard output. This also implies VERBOSE=1.
Monday, August 11, 2014
Relevant courses in Math Dept.
- Taught by Professor Philip E. Gill in 2013 (course link)
- NOTE: Not offered in 2014
- Offered and taught by Professor Nie in 2014
- Mostly concepts in convex optimization covered in ECE 273 by Prof. Lanckriet
- Offered and taught by Professors {Saab, Leok} in 2014
- Not sure how applicable this is to the area of optimization
- Differential geometric and theory of Lie groups (methods used in the paper by Steven Simon and Aris Moustakas to obtain capacity of MIMO correlated channels)
- Taught by Prof. Kemp (who also taught Random Matrix theory course)
Monday, July 28, 2014
Thursday, July 17, 2014
Monday, July 14, 2014
Notes from David and Goliath
- You have to be "desperate enough" to re-frame your disadvantages into attributes that gives you advantages
- From AI for the game of Go, statistical (Monte Carlo methods) evaluation may have a better chance of winning when the search space is indefeasibly large.
Monday, July 07, 2014
Notes on my Ubuntu 14.04 LTS setup
- Hostname
- sudo gvim /etc/hostname
- sudo gvim /etc/hosts
- Samba server
- sudo apt-get install samba
- sudo gvim /etc/samba/smb.conf
# Comment out password database stuff # Add user name map security = user encrypt passwords = true username map = /etc/samba/smbusers
[homes] comment = Home Directories browseable = no read only = no create mask = 0644 directory mask = 0755
- RStudio (IDE for R)
- sudo apt-get install libjpeg62
- sudo dpkg -i rstudio-rel_num-amd64.deb
- Spyder (IDE for python)
Wednesday, July 02, 2014
Building clang
Tuesday, June 24, 2014
R cheatsheet
- install.packages("package_name",dependencies = TRUE) # install package
- library(package_name) # load package
- search() # list all packages attached
- ls() # list all objects in environment/package
- help(name) # help on package/function
- getwd() # get working directory
- list.files() # list files in working directory
- save.image() # save workspace to .Rdata
- savehistory() # save history to .Rhistory
- class(obj) # class of object
- dim() # dimension of matrix
- length() # length of array
- factor() # encode categorical variables using numeric storage (e.g. "red","orange","green")
Monday, June 23, 2014
Wish List for matlab parser
- Add parsing of 1-D and 2-D arrays
- Register params
- Attach to ParseTree
- Look up value based on hierarchical position of params
- Hierarchical file names
- Header to include attributes and formats
Friday, January 10, 2014
Matlab parser notes
Matlab Grammar
statements = statements (statements)*
statement = declare | assign | expr
clear = 'clear' id';'
declare = 'global' id ';'
assign = var '=' ( list | string | expr ) ';'
var = id('.'id)* | id '(' expr (',' expr)* ')'
literal = integer | float
list = '[' expr (',' expr)* ']'
expr = add_expr
add_expr = mul_expr (('+'|'-') mul_expr )*
mul_expr = primary (('*'|'/') primary )*
primary = '(' expr ')' | var | list | literal | '-' primary
Token definition
string = '[char]*' integer = [0:9] float = ...
Operator Precedence
You can build expressions that use any combination of arithmetic, relational, and logical operators. Precedence levels determine the order in which MATLAB® evaluates an expression. Within each precedence level, operators have equal precedence and are evaluated from left to right. The precedence rules for MATLAB operators are shown in this list, ordered from highest precedence level to lowest precedence level:- Parentheses ()
- Transpose (.'), power (.^), complex conjugate transpose ('), matrix power (^)
- Unary plus (+), unary minus (-), logical negation (~)
- Multiplication (.*), right division (./), left division (.\), matrix multiplication (*), matrix right division (/), matrix left division (\)
- Addition (+), subtraction (-)
- Colon operator (:)
- Less than (<), less than or equal to (<=), greater than (>), greater than or equal to (>=), equal to (==), not equal to (~=)
- Element-wise AND (&)
- Element-wise OR (|)
- Short-circuit AND (&&)
- Short-circuit OR (||)
Associativity of operators
- power (.^) is left associative in Matlab
Thursday, January 09, 2014
Compressed sensing notes
- Classical sampling theory (Nyquist-Shannon framework)
- Infinite length, continuous-time signals
- Requires the sample at specific point in time
- Signal recovery in the form of linear sinc interpolation
- Compressed sensing framework
- Finite-dimensional vectors in \(\mathbb{R}^n \)
- Acquires measurements in the form of an inner-products between the signal and a test function
- Signal recovery achieved using highly nonlinear methods
Wednesday, January 08, 2014
Trying out Math on Blogger
Trying \(x_1 = 3\)
\begin{equation} \int_a^b \! f(x) \, \mathrm{d}x \label{eq.gaussian} \end{equation} which we can later refer back to as \eqref{eq.gaussian}.
In equation \eqref{eq:sample}, we find the value of an interesting integral:
\begin{equation} \int_0^\infty \frac{x^3}{e^x-1}\,dx = \frac{\pi^4}{15} \label{eq:sample} \end{equation} Very cool indeed.
Friday, December 28, 2012
Properties of a positive definite matrix
Given an Hermitian matrix M
- The eigenvalues of M is strictly positive.
- It is the Gram matrix of linearly independent vectors.
- It has a Cholesky decomposition. M = M' = L' * L = H' * H. Where L is a triangular matrix with strictly positive diagonal elements.
Sunday, October 07, 2012
Monday, September 24, 2012
Ideal parent of a high reactive child
Someone who can read your cues and respect your individuality; is warm and firm in placing demands on you without being harsh or hostile; promotes curiosity, academic achievement, delayed gratification, and self-control; and is not harsh, neglectful, or inconsistent.
Wednesday, August 29, 2012
Sequence alignment paper
Dynamic programming and sequence alignment
Sunday, August 26, 2012
Paper from Todd Veldhuizen
Techniques for Scientific C++
Wednesday, March 07, 2012
Thursday, May 27, 2010
More setbacks
Thursday, January 28, 2010
Monday, December 21, 2009
Wednesday, September 30, 2009
Workload
Now I'm taking a step back and make sure I will not lead myself astray but trust the guidance of an expert more experienced than I am.
Anyway. It's complex.
Friday, August 21, 2009
How do you get gigabit per second over the air?
- Multiple bits per symbol is a given; there is simply no technology out there that can digitize at gigasample per second.
- Multiple antenna - how do you pack up to four antenna to a device? I can picture that being possible on a decent sized laptop, at 5GHz or more, over short distance with a favourable channel.
- Getting gigabits to the home. This becomes a question of what type of infrastructure is required to do just that. Fiber to the home, and a wireless access point (femtocell). A cell tower managing hundreds of gigabits of data over the air will be challenging.
- A lot has to take place, similar to idea of fuel cell vehicles. Infrastructure is a significant issue.
Saturday, August 08, 2009
Simulations
Friday, August 07, 2009
Survey of the disciplines in communications research
- Information theory
- Coding theory
- Dectection theory
- Control theory
- Network theory
- Computation theory
- Game theory
- Linear systems and signals
- Statistics and random processes
- Antenna & wave propagation
- Large Deviation Theory
- Importance sampling
- DSP and alogrithms
- RF/Microwave circuits
- Embedded systems
Thursday, August 06, 2009
Illustrations in Latex documents
One expensive choice is Adobe Illustrator + MathType. Even at student price, Illustrator is still prohibitively $$$.
A good contender is Inkscape but it's not mature enough for dealing with importing eps equations and editing them in place.
Monday, July 27, 2009
Library barcode system
- My old Toshiba Portege A100 laptop
- Metrologic MS9540 (part of Honeywell) - $150
- Barcode labels (1000 labels) -$28
- Symbology: code 3 of 9, 5-6 Characters, no check code
- Heading: "Mira Mesa Chinese Baptist Church"
- Sequence: nnnnn (n = 0-9, e.g. 01234)
Saturday, July 25, 2009
Testing formulas
The LaTex Equation Editor website is here
Thursday, July 02, 2009
Sunday, June 07, 2009
Friday, April 03, 2009
Thought record
Thursday, July 31, 2008
Saturday, July 05, 2008
LA Restaurants
Taiwanese
Irvine, CA 92720
949-786-3585
July 19, 2008
The Kitchen
203 West Valley Blvd.
Alhambra, CA 91801
626-289-4828
Upscale chinese cuisine, relatively speaking. Great food.
Tasty Garden
288 West Valley Blvd.
Alhambra, CA 91801
626-300-8262
July 4, 2008
Din Tai Fung
1108 South Baldwin Avenue (First store)
1088 South Baldwin Avenue (New, larger, modern looking)
Arcadia, CA 91007
626-574-7068
Phoenix Food Boutique
1108 South Baldwin Avenue
Arcadia, CA 91007
626-284-2388
Beside the drinks, casual food, it has amazingly tasty curry fish balls, not to be missed.
Friday, May 16, 2008
SD Restaurants
737 Pearl St. Suite 110
Lanna Thai Cruisine
4501 Mission Bay Dr.
San Diego, CA 92109
858-274-8424
Tajima Japanese Restaurant
4681 Convoy St
San Diego, CA 92111
(858) 576-7244
Curry House - Japanese style curry and spaghetti
3860 Convoy St. #102
San Diego, CA 92111
(858) 278-2454
Ichiro Japanese Restuarant
4344 Convoy St # Q
San Diego, CA 92111
(858) 565-8603
Lorna's Italian Kitchen
3945 Governer Drive
San Diego, CA 92122
858-452-0661
Dae Jang Keum (Korean fine Cuisine)
7905 Engineer Rd.
San Diego, CA 92111
858-573-2585
Sante Ristorante (Italian) - May 17, 2008
Located at an inside street in La Jolla, not that busy compared to the ones along the coast. But this is a Gem that cannot be missed. Excellent seafood pasta, and delicious tartufo. Highly recommend.
7811 Herschel Avenue
La Jolla, CA
858-454-1315
KI sushi - May 14, 2008
I like the atmosphere and lunch is not bad for the price you pay.
Costa Verde Shopping Center
8650 Genesee Ave
San Diego, CA 92122
Cafe Coyote - May 4, 2008
Great taste of Margaritas and Mexican food.
2461 San Diego Avenue
San Diego, CA 92110
Osetra - May 1, 2008
Gorgeous and modern ambiance with a spectacular 3 storey wine collection and suspension lift for getting the wine! Expensive place, but well worth a visit. Thanks Shirley for bringing me there!
904 5th Avenue, San Diego, CA 92101
Gaslamp Quarters
Wednesday, April 30, 2008
The art of moving...
I understand now how much my dad had to go through when he moved our entire family over. That must have been a feat of enormous proportion. He moved into a completely new culture with a different governing system. But I had no idea at the time, since I was still trying to understand why we moved and coping with adjusting to yet another move in my young life - I was 14 and rebellious.
From HK to England, to Toronto, to Waterloo, to Ottawa, there was not once that I had company while I moved. From Ottawa to Waterloo, and now Waterloo to San Diego, I'm going solo. The lesson I learned from this is that a modern mercenary has to be mobile as ever. You simply cannot keep too many things.
Wednesday, April 23, 2008
Piotr Wozniak's prescription to becoming a genius
Clarify your goals, gain knowledge through spaced repetition, preserve health, work steadily, minimize stress, refuse interruption, and never resist sleep when tired. This should lead to radically improved intelligence and creativity.
Friday, April 18, 2008
Wednesday, April 02, 2008
Items for sale
- Black and Decker Toaster oven
- Car pedal lock
- Propane camping lamp
- Little Green portable wet vacuum
- Cricket stuff
- 2 Supersoaker water guns
- Hockey Gear
- Fishing rod
- PS2 steering wheel
- 2 Sleeping bags and mats
- camping chairs
- 6 foot folding table
- Inflatable sofa and mattress
- Camping tent for 4
- Bauer Roller blades size 8 1/2
- Michelin Pilot Alpin snow tires on steel rims 195/65/15 + hubcabs
- Broil-Mate 50K BTU Gas barbecue (Natural Gas) with stainless steel utensils
- Worx 13A 16" Mulching and bagging electric lawn mower, handle folds down
- 16 foot extension ladder
- Lawn rake, leaf scraper
- 2 Snow shovels
- 2 SnowZinger magic carpets
- Volley ball, basketball
- 2 Weight adjustable Dumbbells
- Stand-up vacuum
- Wine glasses
- Camera tripod
Sunday, February 10, 2008
Peter Drucker on the Individual in an organization
- Effectiveness must be learned
- Focus on contribution
- Know your strengths and values
- Know your time
- Effective decisions
- Functioning communications
- Leadership as work
- Principles of innovation
- The second half of your life
- The educated person
Saturday, December 22, 2007
Reflections on 2007
I have to fight another severe episode of depression. Luckily, I have the help of my dad's friend and a renowned psychiatrist Dr. Wong. He came to the rescue in April and I was fortunate to receive treatment immediately in April. I have been doing quite well now, continuing taking anti-depressant, and I have also kept in constant contact with a local psychiatrist and a very good psychologist in case I needed immediate attention. It's funny how my doc parallel this condition to a diabetic, but again, I am more fortunate than a diabetic because I don't necessarily have to be on medication all my life.
At work, I have created a comfortable environment for myself and I am working quite autonomously. I have gain much respect from my peers so there is now synergy at work, I am spending much less time working on issues.
I have been continuing my goal to establish myself in the soccer field. I am happy to say I have succeeded by being promoted to captain for our dept soccer team for next year. Although my ultimate goal is to coach little kids, not big kids, but it's one small step closer to my goal.
I am continuing my work helping people around me and helping the students at KWCAC. They are a handful but I think I am now enjoying my time helping them. It's a very satisfying experience.
Lucinda has been my big sister and continue to have strong influence on me in my quest to become godly. She is a wonderful person and I will learn much from her.
All my brothers are now in North America, within an hour flight from each other. I think this is the start of something tremendous as we can co-ordinate our activities with much more efficiency than before.
I am looking forward to 2008 as I believe this will be the turning point of my life and the lives of the people I care and love.
Sunday, September 16, 2007
CIBC visa transaction
Received call: approx. 12:30PM
Transaction proceeded 11:01AM
Transaction declined 4:13PM
Best buy order number 5956664
Tuesday, August 07, 2007
Rental agreement - draft
- Share use of kitchen and laundry facilities
- Hydro, heat, water included?
- Phone, TV, cable
- blah blah blah...
Sunday, June 17, 2007
Waterloo weekend getaway
- Saturday night - German food at the Heidenberg http://www.oldhh.com/rest.html
- Games at my place.
Stratford - Sunday noon - brunch at the church restaurant, http://www.churchrestaurant
- Sunday afternoon - stroll at the swan river park, or catch a theater show
- Return home
Useful links:
Stratford dining ideas
Waterloo dining ideas
Wednesday, June 06, 2007
Long distance plan
Distributel http://www.distributel.ca
Onlinetel(Call zone) http://www.onlinetel.com
Tuesday, December 19, 2006
Tuesday, November 14, 2006
Sunday, October 15, 2006
Restaurants in Waterloo region
- Sole, Waterloo (pronounced soliel, french) - pretty good, decent price
- Thai Coconut Island, Cambridge - cheap, but shabby place and food.
- Verses, Kitchener - best restaurant in town, pricey
- Charcoal Steak House, Kitchener
- Chefs on King, Kitchener
- King Crab, Kitchener
- Modern India, Kitchener
Tuesday, September 26, 2006
Gvim custom settings
colors blue
set guifont=Lucida_Console:h10:cANSI
set lines=50
" RIM coding style - 4 characters indents, no tabs
set tabstop=4
set shiftwidth=4
set expandtab
" tags file search
set tags=tags;/
" smart search
set ignorecase
set smartcase
" taglist hotkey - needs taglist.vim installed
" - which needs ctags installed
" - see www.vim.org for details
map
" syntax fold
set foldmethod=syntax
set nofoldenable
" End of Custom settings
Saturday, September 23, 2006
Hitting the 100,000 milestone
Monday, September 18, 2006
In this together
- If you arrive at work in a bad mood, leave it at the door.
- When offered a juicy bit 0f gossip at work, refuse to hear it.
- Always do what you say you will do. Promise management.
- Avoid and stop potential offensive dialog regarding sex, politics, religions.
- The rule when it comes to sexual atttraction at work - Don't look, don't touch.
- Keep private about your opinions.
- "Please and thank you" at work is commom courtesy.
Sunday, September 10, 2006
Air Canada
Date: Sept 10, 2006 7:15am
Location: Ottawa International Airport
Boarded flight:
AC 443 departing Ottawa 8am
Employee badge number:
Air Canada counter clerk
05/2009
1/UC
YOW/100597
Employee physical appearance:
Appeared to be in senior role
White male, grey hair - in his 50s
- Client Checks bag in. Small carry on lugguge, weighs approx. 2 pounds
- Placed bag next to counter clerk within clerk's arm reach
- Bag oriented in inconevient position
- Clerk asked client to have bag flipped
- Client responded with "The bag weighs 2 pounds", and obliged to flip bag
- Clerk obviously offended by the tongue-in-cheek comment, and acted in retaliation
- Clerk refused to process e-ticket and boarding pass - his commited duty as he offered to serve client
- Clerk intentionally made client wait in another line, without giving reason
- Client asked for name/identification from Clerk, Clerk refused to provide identification voluntorily
- Boarding pass smoothly processed by another counter clerk after waiting in another line.
- Client had to note down badge number when the contents of clerk's badge was desernible.
- Client was greeted by RCMPs at the security line, apparently clerk persisted in his retaliatory actions by reporting this as an "incident" to the RCMPs. He further distorted the situation and made the RCMP believe client is an "eratic" individual that may cause harm to the public.
- Besides the agitated clerk, all other individuals that had dealt with client find client to be behaving in good manner. This includes the second client that processed the boarding pass, the RCMPs, the security station staff, the attendent at the boarding gate, the attendents on the plane.
- This leads to the only conclusion that clerk is acting inappropriately and with intent to cause harm to others and refusing to fulfill his duty.
- This behaviour is dangerous, counter productive and damages the reputation of the company the clerk represents. The clerk is in no way fit for client serving duties.
- Client demands 1) the clerk be disciplined appropriately 2) Clerk be removed from active client serving duties 3) a formal apology be given by Air Canada to permit this behaviour in crucial client interaction roles.
Tuesday, August 15, 2006
Ability model of emotional intelligence
- Read People-Identify Emotions: This refers to the ability to identify accurately how you, and those around you, are feeling and your ability to express these feelings. More than awareness, this ability stresses accuracy of awareness.
- Get in the Modd-Use Emotions: This special ability helps you determine how emotions help you and how they work in harmony with thinking. Your ability to use emotions changes your perspective, allowing you to see the world in different ways and to fell what others feel.
- Predict the Emotional Future-Understand Emotions: Emotions have their own language, and they have their own logical moves. The ability to understand emotion means that y ou can determine why you feel the way you do and what will happen next.
- Do It with Feeling-Manage Emotions: Emotinos convey important information, so it is valuable to be open to our emotions and to use this information to make informed decisions.
Monday, July 24, 2006
Sunday, July 16, 2006
Tuesday, July 11, 2006
Bond prices
The central tenet of Bond Market investing is that prices and yields move in opposite directions. Bond prices go up when Bond yields go down, and vice-versa.
Pursuant to this relationship, Bonds are often considered "counter-cyclical" securities, meaning that Bond prices tend to be high and yields tend to be low when the economy's performance is poor. This factor is probably the single most important reason for having some Bonds in your portfolio.
Though there is a great deal of overlap, distinction needs to be made between factors affecting interest rates and factors affecting the price of an individual bond. Interest rates shift in response to a number of factors including: the demand and supply for credit, Federal Reserve policy (monetary policy), fiscal policy (government budgeting and expenditures), tax policy, exchange rates, general economic conditions, price inflation, perceptions and forecasts for future inflation and a host of lesser factors.
Individual Bond prices are not only affected by all of these factors, but additional ones as well. These factors include: supply and demand for the specific issue, liquidity of the issue, special characteristics of the issue, credit quality, perceptions and forecasts for changes in credit quality and a host of lesser factors.
Sunday, July 09, 2006
Soccer balls
Wednesday, July 05, 2006
Tuesday, July 04, 2006
Debt free!
Monday, June 26, 2006
Software manager's checklist
- Do you have your customer's requirements?
- Do you have a n approved budget?
- Do you have an approved roadmap?
- Do you avhe an approved schedule?
- Are you delivering the product on time?
- Do you hire developers in a timely fashion?
- Is your team capable of dealing wiht change?
- Are you capable of keeping your team focused and resisting change?
- Do your customers encounter a lot of quality issues with released products?
- Do you and your team measure how well you do your work on a regular basis to find ways to improve?
- Does your team understand your company's strategy?
- Does your team understand engineering's roadmap?
- Does your team understand why the roadmap meets the goals of the strategy?
- Do you have regular communication meetings and e-mail with your team?
- Are people on y our team willing to tell you bad news?
- Do you hear information about your team from your team before you hear it from others?
- Do members of your team communicate with each other and the rest of the company in a respectful manner?
- Do you provide information to your boss before he or she has to ask for it?
- Do other people in the company know what your team is doing and accomplishing?
- Do you communicate in a positive fashion?
- Does your team develop and buy into their schedules?
- Do you avoid micromanagement?
- Do you delagate tasks and let your reports proceed without interference?
- Do you make it clear what your employees are accountable for?
- Do you provide leadership opportunities for your employees?
- Does your team have a sense of urgency in addressing issues?
- Do you set cleawr roles and responsibilities for your employees?
- Do all the members in your team know what they need to accomplish each week before they can go home fo the weekend?
- Do your developers consider your organization a positive work environment?
- Resources
- features
- Dates
- Quality
- If you remove too many features, you won't have a competitive product.
- If you add too many features, you won't make your dates.
- If you scrimp on quality, you'll get a bad reputation.
- If you wait until the product is prefect, you'll miss the market window.
- If you make your engineers work extra hours all the time, they'll burn out.
- If you add too many resources , you can run out of money.
- If you slip the schedule, you make it hard for the sales team to sell and you might miss a market window.
Thursday, May 11, 2006
Core Competencies of Web 2.0 Companies
- Services, not packaged software, with cost-effective scalability
- Control over unique, hard-to-recreate data sources that get richer as more people use them
- Trusting users as co-developers
- Harnessing collective intelligence
- Leveraging the long tail through customer self-service
- Software above the level of a single device
- Lightweight user interfaces, development models, AND business models
Web 2.0 Design Patterns
- The Long Tail
Small sites make up the bulk of the internet's content; narrow niches make up the bulk of internet's the possible applications. Therefore: Leverage customer-self service and algorithmic data management to reach out to the entire web, to the edges and not just the center, to the long tail and not just the head. - Data is the Next Intel Inside
Applications are increasingly data-driven. Therefore: For competitive advantage, seek to own a unique, hard-to-recreate source of data. - Users Add Value
The key to competitive advantage in internet applications is the extent to which users add their own data to that which you provide. Therefore: Don't restrict your "architecture of participation" to software development. Involve your users both implicitly and explicitly in adding value to your application. - Network Effects by Default
Only a small percentage of users will go to the trouble of adding value to your application. Therefore: Set inclusive defaults for aggregating user data as a side-effect of their use of the application. - Some Rights Reserved. Intellectual property protection limits re-use and prevents experimentation. Therefore: When benefits come from collective adoption, not private restriction, make sure that barriers to adoption are low. Follow existing standards, and use licenses with as few restrictions as possible. Design for "hackability" and "remixability."
- The Perpetual Beta
When devices and programs are connected to the internet, applications are no longer software artifacts, they are ongoing services. Therefore: Don't package up new features into monolithic releases, but instead add them on a regular basis as part of the normal user experience. Engage your users as real-time testers, and instrument the service so that you know how people use the new features. - Cooperate, Don't Control
Web 2.0 applications are built of a network of cooperating data services. Therefore: Offer web services interfaces and content syndication, and re-use the data services of others. Support lightweight programming models that allow for loosely-coupled systems. - Software Above the Level of a Single Device
The PC is no longer the only access device for internet applications, and applications that are limited to a single device are less valuable than those that are connected. Therefore: Design your application from the get-go to integrate services across handheld devices, PCs, and internet servers.





