壓縮感知
Compressed sensing
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3 10:10–11:00 | 壓縮感知 SA213（光復） 2 節連堂 | |
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7 15:30–16:20 | 壓縮感知 SA213（光復） |
* 根據陽明交大上課時間表所列
Compressed sensing aims to recover a sparse signal from a small number of linear measurements, which are obtained by multiplying the signal by a sensing matrix and taking the inner product with a set of basis vectors. The problem can be treated as find the solution of an under determined linear system which has the smallest number of nonzero element.
Linear Algebra, Probability, Mathematical Analysis
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You can find more and useful material from this URL https://dsp.rice.edu/cs/
Homework: 40% Project: 30% Final Exam: 30%
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| 第 1 週 | Preparing week |
| 第 2 週 | Mathematical background |
| 第 3 週 | Basic Information Theorey |
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1. S. Boyd, N. Parikh, E. Chu, B. Peleato, and J. Eckstein. "Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers", Foundations and Trends in Machine Learning, 3(1): 1–122, 2011. 2. Kurt Bryan, and Tanya Leise. "Making Do with Less: AnIntroductionto CompressedSensing" , SIAM REVIEW Vol. 55, No.3, pp.547–566, 2013
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- Email: yuhjye@math.nctu.edu.tw