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THE HIGH ORDER BLOCK RIP CONDITION FOR SIGNAL RECOVERY 被引量:5

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摘要 In this paper,we consider the recovery of block sparse signals,whose nonzero entries appear in blocks (or clusters)rather than spread arbitrarily throughout the signal,from incomplete linear measurements.A high order sufficient condition based on block RIP is obtained to guarantee the stable recovery of all block sparse signals in the presence of noise,and robust recovery when signals are not exactly block sparse via mixed l2/l1 minimization.Moreover,a concrete example is established to ensure the condition is sharp.The significance of the results presented in this paper lies in the fact that recovery may be possible under more general conditions by exploiting the block structure of the sparsity pattern instead of the conventional sparsity pattern.
出处 《Journal of Computational Mathematics》 SCIE CSCD 2019年第1期61-75,共15页 计算数学(英文)
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  • 1Baraniuk, R., Cevher, V., Durate, M., et al.: Model based compressive sensing. IEEE Trans. Inform. Theory, 56, 1982-2001 (2010).
  • 2Cai, T., Wang, L., Xu, G.: New bounds for restricted isometry constants. IEEE Trans. Inform. Theory, 56, 4388-4394 (2010).
  • 3Cai, T., Wang, L., Zhang, J.: Shifting inequality and recovery of sparse signals. IEEE Trans. Inform. Theory, 58, 1300-1308 (2010).
  • 4Candhs, E. J.: The restricted isometry property and its implications for compressed sensing. C.R. Math. Acad. Sci. Paris, Serie I, 346, 589-592 (2008).
  • 5Cands, E. J., Romberg, J., Tao, T.: Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information. IEEE Trans. Inform. Theory, 52,489-509 (2006).
  • 6Cands, E. J., Romberg, J., Tao, T.: Stable signal recovery from incomplete and inaccurate measurements. Comm. Pure Appl. Math., 59, 1207-1223 (2006).
  • 7Cands, E. J., Tao, T.: Decoding by linear programming. IEEE Trans. Inform. Theory, 51, 4203-4215 (2005).
  • 8Davies, M. E., Gribonval, R.: Restricted isometry properties where lp sparse recovery can fail for 0 < p _< 1. IEEE Trans. Inform. Theory, 55, 2203-2214 (2010).
  • 9Donoho, D.: Compressed sensing. IEEE Trans. Inform. Theory, 52, 1289-1306 (2006).
  • 10Eldar, Y. C., Kuppinger, P., Bolcskei, H.: Block-sparse signals: uncertainty relations and efficient recovery. IEEE Trans. Signal Process., 58, 3042-3054 (2010).

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