compressive sensing

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(Mühendislik) Compressed sensing, also known as compressive sensing, compressive sampling and sparse sampling, is a technique for finding sparse solutions to underdetermined linear systems. In engineering, it is the process of acquiring and reconstructing a signal utilizing the prior knowledge that it is sparse or compressible. The field has existed for at least four decades, but recently the field has exploded, in part due to several important results by David Donoho, Emmanuel Candès, Justin Romberg and Terence Tao
Originally proposed by Emmanuel Candes and Terrence Tao, compressive sensing aims to sample signals sparsely in transform domains. The sparse samples may be decoded into the original signal under certain conditions
compressive sensing
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