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Volumn , Issue , 2017, Pages 2272-2276

Learning to invert: Signal recovery via Deep Convolutional Networks

Author keywords

Compressive Sensing; Convolutional Neural Networks; Deep Learning

Indexed keywords


EID: 85023744403     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2017.7952561     Document Type: Conference Paper
Times cited : (322)

References (18)
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    • Donoho, D.L.1
  • 4
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    • Near-optimal signal recovery from random projections: Universal encoding strategies?
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    • Messagepassing algorithms for compressed sensing
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    • Donoho, D.L.1    Maleki, A.2    Montanari, A.3
  • 6
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    • Cosamp: Iterative signal recovery from incomplete and inaccurate samples
    • D. Needell and J. A. Tropp, "Cosamp: Iterative signal recovery from incomplete and inaccurate samples," Appl. Comput. Harmon. Anal., Vol. 26, no. 3, pp. 301-321, 2009.
    • (2009) Appl. Comput. Harmon. Anal. , vol.26 , Issue.3 , pp. 301-321
    • Needell, D.1    Tropp, J.A.2
  • 8
    • 77951100868 scopus 로고    scopus 로고
    • Learning to sense sparse signals: Simultaneous sensing matrix and sparsifying dictionary optimization
    • J. M. Duarte-Carvajalino and G. Sapiro, "Learning to sense sparse signals: Simultaneous sensing matrix and sparsifying dictionary optimization," Tech. Rep., DTIC Document, 2008.
    • (2008) Tech. Rep., DTIC Document
    • Duarte-Carvajalino, J.M.1    Sapiro, G.2
  • 9
    • 33750383209 scopus 로고    scopus 로고
    • K-SVD: An algorithm for designing overcomplete dictionaries for sparse representation
    • M. Aharon, M. Elad, and A. Bruckstein, "K-SVD: An algorithm for designing overcomplete dictionaries for sparse representation," IEEE Trans. Signal Processing, Vol. 54, no. 11, pp. 4311-4322, 2006.
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    • Aharon, M.1    Elad, M.2    Bruckstein, A.3
  • 16
    • 31744440684 scopus 로고    scopus 로고
    • Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information
    • E. J. Candès, J. Romberg, and T. Tao, "Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information," IEEE Trans. Inform. Theory, Vol. 52, no. 2, pp. 489-509, 2006.
    • (2006) IEEE Trans. Inform. Theory , vol.52 , Issue.2 , pp. 489-509
    • Candès, E.J.1    Romberg, J.2    Tao, T.3
  • 18
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    • The pros and cons of compressive sensing for wideband signal acquisition: Noise folding versus dynamic range
    • M. A. Davenport, J. N Laska, J. R Treichler, and R. G Baraniuk, "The pros and cons of compressive sensing for wideband signal acquisition: Noise folding versus dynamic range," IEEE Trans. Signal Processing, Vol. 60, no. 9, pp. 4628-4642, 2012.
    • (2012) IEEE Trans. Signal Processing , vol.60 , Issue.9 , pp. 4628-4642
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.