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dc.contributor.authorYin, Wotao
Morgan, Simon
Yang, Junfeng
Zhang, Yin
dc.date.accessioned 2018-06-19T17:45:55Z
dc.date.available 2018-06-19T17:45:55Z
dc.date.issued 2010-01
dc.identifier.citation Yin, Wotao, Morgan, Simon, Yang, Junfeng, et al.. "Practical Compressive Sensing with Toeplitz and Circulant Matrices." (2010) https://hdl.handle.net/1911/102144.
dc.identifier.urihttps://hdl.handle.net/1911/102144
dc.description.abstract 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.
dc.format.extent 10 pp
dc.title Practical Compressive Sensing with Toeplitz and Circulant Matrices
dc.type Technical report
dc.date.note January 2010
dc.identifier.digital TR10-01
dc.type.dcmi Text


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