Lecture notes and supplementary materials for PMBED209, Fall 2016

1. lecture 1
   9/26/2016 signal and image representation, sampling and quantization, review of LTI system, impulse response, etc.
   Wiki page on companding quantization.
   Book on nonuniform sampling. Available at UCLA library. A quick browsing over TOC would reveal the scope of work and applications.
   Interactive lecture by Wilson J. Rugh on LTI systems, JHU
   
2. lecture 2
   9/28/2016 Review of basic linear algebra, spans and basis, orthogonal projections, Fourier as a special basis.
   Reference book: Convex optimization by Boyd and Vandenberghe. Also open courseware and online video by Boyd.
   Local resource: Pro. L. Vandenberghe UCLA EE236 series.
   review of linear algebra: Khan Academy.
   
3. lecture 3
   10/3/2016 Continue review of basic linear algebra, spans and basis, orthogonal projections, Fourier as a special basis.
   
4. lecture 4
   10/5/2016 Discussion of sampling theorem and its "conflict" with compressive sensing.
   Collection of tutorials and reviews of comressed sensing: compressive sensing .
   http://dsp.rice.edu/cs
5. lecture 5
   10/12/2016 Least squares regression and projection, statistical estimation.
   
6. lecture 6
   10/14/2016 Minimum norm solution for underdteremined systems. Gauss-Markov model.
   
7. invited lecture by Dr. Henry Huang
   10/19/2016 Tomography a a modeilng problem.
   
8. invited lecture by Dr. Holden Wu
   10/21/2016 Real-time NonCartesian Sampling in MRI.
   
9. invited lecture by Dr. Kyung Sung
   10/26/2016 Advanced MRI reconstruciton iwth compressed sensing.
   
10. lecture 7
    11/4/2016 Eigen values and eigen vectors
    
11. lecture 8
    11/9/2016 Principal component analysis and factor analysis, derivations and intuitions.
    
12. lecture 9
    11/16/2016 Extensions of PCA (robust PCA, probabilistic PCA), independent component analysis.
    
13. lecture 10
    11/18/2016 Algorithms for independent component analysis. Overview for image restoration and reconstruction
    
14. lecture 11
    11/23/2016 Overview of image segmentation, object identification (classification) and registration
    
15. 
    11/25/2016 Thanksgiving break
    
16. 
    11/30/2016 Project presentation (extended hours 8:30-12am)
    

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