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Volumn , Issue , 2009, Pages 684-688

Conditions for recovery of sparse signals correlated by local transforms

Author keywords

Local transforms; Sparse approximations; Thresholding

Indexed keywords

CORRELATED SIGNALS; LOCAL TRANSFORMS; LOW COMPLEXITY; MULTIPLE SENSORS; SPARSE APPROXIMATIONS; SPARSE SIGNALS; SUFFICIENT CONDITIONS; THRESHOLDING;

EID: 70449469716     PISSN: 21578102     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISIT.2009.5205669     Document Type: Conference Paper
Times cited : (3)

References (7)
  • 1
    • 57349143370 scopus 로고    scopus 로고
    • Atoms of all channels, unite! average case analysis of multi-channel sparse recovery using greedy algorithms
    • R. Gribonval, H. Rauhut, K. Schnass, and P. Vandergheynst, "Atoms of all channels, unite! average case analysis of multi-channel sparse recovery using greedy algorithms," Journal of Fourier Analysis and Applications, vol. 14, no. 5, pp. 655-687, 2008.
    • (2008) Journal of Fourier Analysis and Applications , vol.14 , Issue.5 , pp. 655-687
    • Gribonval, R.1    Rauhut, H.2    Schnass, K.3    Vandergheynst, P.4
  • 6
    • 36549074701 scopus 로고    scopus 로고
    • Beyond spars ity: Recovering structured representat ions by 11 minimizat ion and greedy algori thms
    • Gribonval R. and Nielse n M., "Beyond spars ity: Recovering structured representat ions by 11 minimizat ion and greedy algori thms," Advances in computational mathematics, vol. 28, no. 1, pp. 23-41,2008.
    • (2008) Advances in computational mathematics , vol.28 , Issue.1 , pp. 23-41
    • Gribonval, R.1    Nielse n, M.2
  • 7
    • 5444237123 scopus 로고    scopus 로고
    • Greed is good: Algori thm ic resu lts for sparse approximation
    • October
    • J. Tropp, "Greed is good: Algori thm ic resu lts for sparse approximation," IEEE Transactions on Information Theory, vol. 50, no. 10, pp. 2231-2242 , October 2004.
    • (2004) IEEE Transactions on Information Theory , vol.50 , Issue.10 , pp. 2231-2242
    • Tropp, J.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.