Compressive Sensing and Sparse Recovery Lecture 1Oct 14th

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Lecture1 Basis expansion fundamentals • This lecture talks about some fundamental mathematical background which will be quite useful in the subsequent lectures. It mainly focuses on how to represent the signal of interest as a discrete linear combination of basis signals. For orthogonal basis expansions, the generalized Parseval's theorem shows that all signal processing can be done by manipulating discrete sequences of expansion coefficients. This lecture also talks about the Discrete Cosine Transform (DCT) with its applications in image and video compression, and it ends with non-orthogonal bases and overcomplete frames. • Compressive Sensing and Sparse Recovery is a short course taught by Professor Justin Romberg during his visit to Tsinghua University from Oct. 14h to Oct. 18th, 2013. Professor Justin Romberg is an Associate Professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. • More details about the course: http://gu.ee.tsinghua.edu.cn/index.ph...

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