標題: An Improved RIP-Based Performance Guarantee for Sparse Signal Reconstruction via Subspace Pursuit
作者: Chang, Ling-Hua
Wu, Jwo-Yuh
資訊工程學系
電機資訊學士班
Department of Computer Science
Undergraduate Honors Program of Electrical Engineering and Computer Science
關鍵字: Compressive sensing;restricted isometry property (RIP);restricted isometry constant (RIC);subspace pursuit
公開日期: 1-Jan-2014
摘要: Subspace pursuit (SP) is a well-known greedy algorithm capable of reconstructing a sparse signal vector from a set of incomplete measurements. In this paper, by exploiting an approximate orthogonality condition characterized in terms of the achievable angles between two compressed orthogonal sparse vectors, we show that perfect signal recovery in the noiseless case, as well as stable signal recovery in the noisy case, is guaranteed if the sensing matrix satisfies RIP of order 3K with RIC delta(3K) <= 0.2412. Our work improves the best-known existing results, namely, delta(3K) < 0.165 for the noiseless case [3] and delta(3K) < 0.139 when noise is present [4]. In addition, for the noisy case we derive a reconstruction error upper bound, which is shown to be smaller as compared to the bound reported in [4].
URI: http://hdl.handle.net/11536/128565
ISBN: 978-1-4799-1481-4
ISSN: 1551-2282
期刊: 2014 IEEE 8TH SENSOR ARRAY AND MULTICHANNEL SIGNAL PROCESSING WORKSHOP (SAM)
起始頁: 405
結束頁: 408
Appears in Collections:Conferences Paper