dc.contributor.author Yin, WotaoMorgan, SimonYang, JunfengZhang, Yin 2018-06-19T17:45:55Z 2018-06-19T17:45:55Z 2010-01 Yin, Wotao, Morgan, Simon, Yang, Junfeng, et al.. "Practical Compressive Sensing with Toeplitz and Circulant Matrices." (2010) https://hdl.handle.net/1911/102144. https://hdl.handle.net/1911/102144 Compressive sensing encodes a signal into a relatively small number of incoherent linear measurements. In theory, the optimal incoherence is achieved by completely random measurement matrices. However, such matrices are difficult and/or costly to implement in hardware realizations. After summarizing recent results of how random Toeplitz and circulant matrices can be easily (or even naturally) realized in various applications, we introduce fast algorithms for reconstructing signals from incomplete Toeplitz and circulant measurements. We present computational results showing that Toeplitz and circulant matrices are not only as effective as random matrices for signal encoding, but also permit much faster signal decoding. 10 pp Practical Compressive Sensing with Toeplitz and Circulant Matrices Technical report January 2010 TR10-01 Text
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