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Volumn 139, Issue , 2017, Pages 49-61

A gradient-based approach to optimization of compressed sensing systems

Author keywords

Compressive sensing; Mutual coherence; Optimization techniques

Indexed keywords

COMPRESSED SENSING; ITERATIVE METHODS; SIGNAL RECONSTRUCTION;

EID: 85017615947     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.sigpro.2017.04.005     Document Type: Article
Times cited : (18)

References (28)
  • 1
    • 31744440684 scopus 로고    scopus 로고
    • Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
    • [1] Candes, E.J., Romberg, J., Tao, T., Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information. IEEE Trans. Inf. Theory 52:2 (2006), 489–509, 10.1109/TIT.2005.862083.
    • (2006) IEEE Trans. Inf. Theory , vol.52 , Issue.2 , pp. 489-509
    • Candes, E.J.1    Romberg, J.2    Tao, T.3
  • 2
    • 33645712892 scopus 로고    scopus 로고
    • Compressed sensing
    • [2] Donoho, D.L., Compressed sensing. IEEE Trans. Inf. Theory 52:4 (2006), 1289–1306, 10.1109/TIT.2006.871582.
    • (2006) IEEE Trans. Inf. Theory , vol.52 , Issue.4 , pp. 1289-1306
    • Donoho, D.L.1
  • 4
    • 80051736221 scopus 로고    scopus 로고
    • Structured compressed sensing: from theory to applications
    • [4] Duarte, M.F., Eldar, Y.C., Structured compressed sensing: from theory to applications. IEEE Trans. Signal Process. 59:9 (2011), 4053–4085, 10.1109/TSP.2011.2161982.
    • (2011) IEEE Trans. Signal Process. , vol.59 , Issue.9 , pp. 4053-4085
    • Duarte, M.F.1    Eldar, Y.C.2
  • 5
    • 67649842407 scopus 로고    scopus 로고
    • Learning to sense sparse signals: simultaneous sensing matrix and sparsifying dictionary optimization
    • [5] Duarte-Carvajalino, J.M., Sapiro, G., Learning to sense sparse signals: simultaneous sensing matrix and sparsifying dictionary optimization. IEEE Trans. Image Process. 18:7 (2009), 1395–1408, 10.1109/TIP.2009.2022459.
    • (2009) IEEE Trans. Image Process. , vol.18 , Issue.7 , pp. 1395-1408
    • Duarte-Carvajalino, J.M.1    Sapiro, G.2
  • 7
    • 5444237123 scopus 로고    scopus 로고
    • Greed is good: algorithmic results for sparse approximation
    • [7] Tropp, J.A., Greed is good: algorithmic results for sparse approximation. IEEE Trans. Inf. Theory 50:10 (2004), 2231–2242, 10.1109/TIT.2004.834793.
    • (2004) IEEE Trans. Inf. Theory , vol.50 , Issue.10 , pp. 2231-2242
    • Tropp, J.A.1
  • 8
    • 64649083745 scopus 로고    scopus 로고
    • Signal recovery from random measurements via orthogonal matching pursuit
    • [8] Tropp, J.A., Gilbert, A.C., Signal recovery from random measurements via orthogonal matching pursuit. IEEE Trans. Inf. Theory 53:12 (2007), 4655–4666, 10.1109/TIT.2007.909108.
    • (2007) IEEE Trans. Inf. Theory , vol.53 , Issue.12 , pp. 4655-4666
    • Tropp, J.A.1    Gilbert, A.C.2
  • 9
    • 85032750937 scopus 로고    scopus 로고
    • An introduction to compressive sampling
    • [9] Candes, E.J., Wakin, M.B., An introduction to compressive sampling. IEEE Signal Process. Mag. 25:2 (2008), 21–30, 10.1109/MSP.2007.914731.
    • (2008) IEEE Signal Process. Mag. , vol.25 , Issue.2 , pp. 21-30
    • Candes, E.J.1    Wakin, M.B.2
  • 10
    • 85032751460 scopus 로고    scopus 로고
    • 2 optimization in signal and image processing
    • 2 optimization in signal and image processing. IEEE Signal Process. Mag. 27:3 (2010), 76–88, 10.1109/MSP.2010.936023.
    • (2010) IEEE Signal Process. Mag. , vol.27 , Issue.3 , pp. 76-88
    • Zibulevsky, M.1    Elad, M.2
  • 12
    • 84892329327 scopus 로고    scopus 로고
    • Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing
    • Springer New York, NY, USA
    • [12] Elad, M., Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing. 2009, Springer, New York, NY, USA.
    • (2009)
    • Elad, M.1
  • 14
    • 33750383209 scopus 로고    scopus 로고
    • K-SVD: an algorithm for designing overcomplete dictionaries for sparse representation
    • [14] Aharon, M., Elad, M., Bruckstein, A., K-SVD: an algorithm for designing overcomplete dictionaries for sparse representation. IEEE Trans. Signal Process. 54:11 (2006), 4311–4322, 10.1109/TSP.2006.881199.
    • (2006) IEEE Trans. Signal Process. , vol.54 , Issue.11 , pp. 4311-4322
    • Aharon, M.1    Elad, M.2    Bruckstein, A.3
  • 15
    • 84870874964 scopus 로고    scopus 로고
    • Improving dictionary learning: multiple dictionary updates and coefficient reuse
    • [15] Smith, L.N., Elad, M., Improving dictionary learning: multiple dictionary updates and coefficient reuse. IEEE Signal Process. Lett. 20:1 (2013), 79–82, 10.1109/LSP.2012.2229976.
    • (2013) IEEE Signal Process. Lett. , vol.20 , Issue.1 , pp. 79-82
    • Smith, L.N.1    Elad, M.2
  • 16
    • 84877756294 scopus 로고    scopus 로고
    • Dictionary training for sparse representation as generalization of k-means clustering
    • [16] Sahoo, S.K., Makur, A., Dictionary training for sparse representation as generalization of k-means clustering. IEEE Signal Process. Lett. 20:6 (2013), 587–590, 10.1109/LSP.2013.2258912.
    • (2013) IEEE Signal Process. Lett. , vol.20 , Issue.6 , pp. 587-590
    • Sahoo, S.K.1    Makur, A.2
  • 17
    • 36749022762 scopus 로고    scopus 로고
    • Optimized projections for compressed sensing
    • [17] Elad, M., Optimized projections for compressed sensing. IEEE Trans. Signal Process. 55:12 (2007), 5695–5702, 10.1109/TSP.2007.900760.
    • (2007) IEEE Trans. Signal Process. , vol.55 , Issue.12 , pp. 5695-5702
    • Elad, M.1
  • 19
    • 80051751662 scopus 로고    scopus 로고
    • Sensing matrix optimization for block-sparse decoding
    • [19] Zelnik-Manor, L., Rosenblum, K., Eldar, Y.C., Sensing matrix optimization for block-sparse decoding. IEEE Trans. Signal Process. 59:9 (2011), 4300–4312, 10.1109/TSP.2011.2159211.
    • (2011) IEEE Trans. Signal Process. , vol.59 , Issue.9 , pp. 4300-4312
    • Zelnik-Manor, L.1    Rosenblum, K.2    Eldar, Y.C.3
  • 20
    • 84877903708 scopus 로고    scopus 로고
    • On projection matrix optimization for compressive sensing systems
    • [20] Li, G., Zhu, Z., Yang, D., Chang, L., Bai, H., On projection matrix optimization for compressive sensing systems. IEEE Trans. Signal Process. 61:11 (2013), 2887–2898, 10.1109/TSP.2013.2253776.
    • (2013) IEEE Trans. Signal Process. , vol.61 , Issue.11 , pp. 2887-2898
    • Li, G.1    Zhu, Z.2    Yang, D.3    Chang, L.4    Bai, H.5
  • 21
    • 0242323185 scopus 로고    scopus 로고
    • Grassmannian frames with applications to coding and communication
    • [21] Strohmer, T., Heath, R.W., Grassmannian frames with applications to coding and communication. Appl. Comput. Harmon. Anal. 14:3 (2003), 257–275.
    • (2003) Appl. Comput. Harmon. Anal. , vol.14 , Issue.3 , pp. 257-275
    • Strohmer, T.1    Heath, R.W.2
  • 22
    • 0242480130 scopus 로고    scopus 로고
    • An Introduction to Frames and Riesz Bases
    • Birkhäuser Boston, MA
    • [22] Christensen, O., An Introduction to Frames and Riesz Bases. 2003, Birkhäuser, Boston, MA.
    • (2003)
    • Christensen, O.1
  • 23
    • 77956830813 scopus 로고    scopus 로고
    • Optimized projection matrix for compressive sensing
    • [23] Xu, J., Pi, Y., Cao, Z., Optimized projection matrix for compressive sensing. EURASIP J. Adv. Signal Process. 43 (2010), 1–8.
    • (2010) EURASIP J. Adv. Signal Process. , vol.43 , pp. 1-8
    • Xu, J.1    Pi, Y.2    Cao, Z.3
  • 24
    • 83955164191 scopus 로고    scopus 로고
    • A gradient-based alternating minimization approach for optimization of the measurement matrix in compressive sensing
    • [24] Abolghasemi, V., Ferdowsi, S., Sanei, S., A gradient-based alternating minimization approach for optimization of the measurement matrix in compressive sensing. Signal Process. 92:4 (2012), 999–1009.
    • (2012) Signal Process. , vol.92 , Issue.4 , pp. 999-1009
    • Abolghasemi, V.1    Ferdowsi, S.2    Sanei, S.3
  • 25
    • 84924045952 scopus 로고    scopus 로고
    • Alternating optimization of sensing matrix and sparsifying dictionary for compressed sensing
    • [25] Bai, H., Li, G., Li, S., Li, Q., Jiang, Q., Chang, L., Alternating optimization of sensing matrix and sparsifying dictionary for compressed sensing. IEEE Trans. Signal Process. 63:6 (2015), 1581–1594, 10.1109/TSP.2015.2399864.
    • (2015) IEEE Trans. Signal Process. , vol.63 , Issue.6 , pp. 1581-1594
    • Bai, H.1    Li, G.2    Li, S.3    Li, Q.4    Jiang, Q.5    Chang, L.6
  • 26
    • 84943760697 scopus 로고    scopus 로고
    • Designing robust sensing matrix for image compression
    • [26] Li, G., Li, X., Li, S., Bai, H., Jiang, Q., He, X., Designing robust sensing matrix for image compression. IEEE Trans. Image Process. 24:12 (2015), 5389–5400, 10.1109/TIP.2015.2479474.
    • (2015) IEEE Trans. Image Process. , vol.24 , Issue.12 , pp. 5389-5400
    • Li, G.1    Li, X.2    Li, S.3    Bai, H.4    Jiang, Q.5    He, X.6
  • 27
    • 84956881607 scopus 로고    scopus 로고
    • An efficient algorithm for designing projection matrix in compressive sensing based on alternating optimization
    • [27] Hong, T., Bai, H., Li, S., Zhu, Z., An efficient algorithm for designing projection matrix in compressive sensing based on alternating optimization. Signal Process. 125 (2016), 9–20.
    • (2016) Signal Process. , vol.125 , pp. 9-20
    • Hong, T.1    Bai, H.2    Li, S.3    Zhu, Z.4
  • 28
    • 84895927017 scopus 로고    scopus 로고
    • Optimized projections for compressed sensing via rank-constrained nearest correlation matrix
    • [28] Cleju, N., Optimized projections for compressed sensing via rank-constrained nearest correlation matrix. Appl. Computat. Harmon. Anal. 36:3 (2014), 495–507.
    • (2014) Appl. Computat. Harmon. Anal. , vol.36 , Issue.3 , pp. 495-507
    • Cleju, N.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.