Lectures

Cogsci 109 FA07

Home	Announcements	Lectures	Assignments	Instructional Team	Links	Frequently Asked Questions
Textbooks	Grading	Office hours	Handouts	Labs and locations	Course Description

Click the links in the topics column to download pdf of lecture notes.

Current week is highlighted in yellow. Topics may change slightly (or order of topics).

Week	Lecture #	Date	Topics	Description	Section topics	Homework
wk0	1	Fri Sept 28, 2007	Intro and motivation(pdf) Lecture 1 Recording (mp3)	Course organization, contents, logistics, introduction to modelling and data analysis concepts	No section Thursday and Friday (Sept 27 and 28)	Assignment # 1 Due Monday Oct1 07
wk1	2	Mon Oct 1, 2007	Matlab I and math see introductory chapter from Prof. Thomas Bewley's Numerical Methods Book (pdf) Lecture 2 Recording (mp3)	Matlab, math review, basic data manipulation	Matlab, introduction to course resources, starting homework 2	Assignment 2 assigned: Due Mon. Oct. 8, 2007
wk1	3	Wed, Oct 3, 2007	Getting_your_data_slides(pdf) Lecture 3 Recording (mp3)	getting matlab (running remotely), review of programming concepts by demonstration, functions, matlab plots, importing files (ascii, binary, mat) -offer after class review and office hours of programming, math homework, improving remote speed, basic data visualization, fileIO, memory, toolboxes	Matlab, introduction to course resources
wk1	4	Fri, Oct 5, 2007	Data Analysis I (pdf) Lecture 4 Recording (mp3) (see handouts section for sample code)	Analog vs. Digital, Continuous/Discrete, digitization, sampling, aliasing, filtering (low pass and high pass), two simple easy filters	Matlab, introduction to course resources
wk2	5	Mon. Oct 8 2007	Data Analysis II (pdf)	More on the dot operator, matlab tips. Discretization examples. Aliasing examples. Filtering theory, matlab functions	More Matlab plotting, math review. Loading data and saving data. Sorting, dealing with types of data
wk2	6	Wed Oct 10, 2007	Data Analysis III (pdf)	Fourier Transforms - examples, equations, and code, linearity/nonlinearity, more frequency response, moving average filter, recursive filter, low pass and high pass versions	More Matlab plotting, math review. Loading data and saving data. Sorting, dealing with types of data
wk2	7	Fri Oct 12, 2007	Color theory, visualization slides I (pdf)	Effective visualization, color maps, perception, good presentation, demonstrations, CIE Chromaticity, RGB, CMY, CMYK, HSV, False color representation, color constancy, basic occular physiology	More Matlab plotting, math review. Loading data and saving data. Sorting, dealing with types of data
wk3	8	Mon. Oct 15, 2007	Color theory, visulization II,		Visualization	Assignment 3 assigned, due Oct 29, Mon
wk3	9	Wed, Oct 17, 2007	Color examples, Standard statistics and more - mean, median(pdf)	plus super/subsampling	Visualization
wk3	10	Fri, Oct 19, 2007	Stats. examples, variability measure, variance, range, standard deviation, and more (pdf)		Visualization
wk4	11	Mon. Oct 22, 2007	No class - campus closure due to San Diego Wildfires		No section
wk4	12	Wed. Oct 24, 2007	No class - campus closure due to San Diego Wildfires		No section
wk4	13	Fri. Oct. 26, 2007	No class - campus closure due to San Diego Wildfires		No section
wk5	14	Mon. Oct 29, 2007	smooth colormaps and linear least squares (pdf) Handout for linear least squares partial differential equation derivation(pdf)		Stats, homework discussion, matlab examples	Assignment 3 due, see FAQ page for answers to common questions
wk5	15	Wed, Oct 31, 2007	linear vs. affine systems, linear equations, nonlinear least squares (polynomial fits), overfitting(pdf)	plus matlab implementation, discussion of the midterm, next assignment timing, and announcement of midterm review	Stats, homework discussion, matlab examples
wk5	16	Fri, Nov 2, 2007	correlation (pdf)	Interpolation is an important concept for numerical integration and differentiation. There are many forms of interpolation, one group of which we've seen with least squares. Here we see another group, examples, and matlab implementation. How to LERP, BERP, TERP, and SLERP the right way.	Stats, homework discussion, matlab examples
wk6	17	Mon Nov 5, 2007	Slides(pdf)	SLERP, linear interpolation LERP, bilinear interpolation BERP, trilinear interpolation TERP, spherical linear interpolation, lagrange, splines, homework announcement	least squares, more stats examples
wk6	18	Wed Nov 7, 2007	lagrange interpolation (pdf)	(how good is your model?) The concept of error as uncertainty. Splines introduction
wk6	19	Fri Nov. 9, 2007	Midterm Midterm review topics(pdf) practice midterm(pdf) practice midterm solutions(pdf)
wk7	20	Mon, Nov 12, 2007	NO LECTURE - VETERAN'S DAY		NO SECTION MONDAY - VETERAN'S DAY
wk7	21	Wed, Nov 14, 2007	Lagrange examples, Splines (pdf)		homework/midterm review
wk7	22	Fri Nov 16, 2007	error analysis(pdf)		homework/midterm review
wk8	23	Mon Nov 19 2007	optimization, introduction creatures demo (mpeg) ~9MB example code from lecture... nlf.m myfitfunslow.m	Nonlinear function fitting of functions with nonlinear parameters. Nelder-Mead Simplex method (FMINSEARCH IN MATLAB)	error analysis, uncertainty, examples
wk8	24	Wed, Nov 21, 2007	optimization, gradient descent, conjugate gradient concepts (pdf) more Nelder-Mead details	Review of course up to now, course organization and progress report (you're doing well!), project discussion, optimization, method of steepest descent, conjugate gradient review of homework 5, hints,	gradient descent, homework review
wk8		Fri Nov 23, 2007	Thanksgiving vacation	NO CLASS THURSDAY!!!	no section
wk9	25	Mon Nov 26 2007	gradient descent mathematical specifics, extension to conjugate gradient, examples (pdf)		gradient descent, nonlinear function fits, homework review
wk9	26	Wed Nov 28 2007	Intro to neural networks I - the TLU and perceptrons single_neuron.m	conceptual introduction to neural networks Threshold logic units, the history of neural networks, and perceptrons, as well as examples, neural networks for boolean logic, failures of single neurons to solve all possible problems	gradient descent, nonlinear function fits, homework review
wk9	27	Fri Nov 30 2007	Intro to ANN's II (pdf) Little Dog Video (AVI) Big Dog Video (WMV) inverted pendulum video (MPEG)	Modern neural network theory, multi-layer networks, examples, some common structures and modeling methods, function fitting and classification, if time	gradient descent, nonlinear function fits, homework review
wk10	28	Mon Dec 3 2007	Intro to ANN's III Training issues in ANN's, unsupervised learning,reinforcement learning	improving weight convergence, avoiding overfitting	single and multi-layer ANN's, review, sorting out homework/midterm issues
wk10	29	Wed Dec 5 2007	Intro to ANN's IV Associative memory, hebbian learning, hopfield networks	unsupervised learning, hopfield networks	single and multi-layer ANN's, review, sorting out homework/midterm issues	Homework 6 assigned
wk10	30	Fri Dec 7 2007	review and AI introduction, closing remarks, where to go from here(pdf)	AI search methods in addition, hypothesis testing, reading results in papers (Heuristics, A*, etc)	single and multi-layer ANN's, review, sorting out homework/midterm issues