ON THE DESIGN OF OPTIMIZED PROJECTIONS FOR SENSING SPARSE SIGNALS IN OVERCOMPLETE DICTIONARIES

被引：0

作者：

Chen, Wei ^{[1
]}

Rodrigues, Miguel R. D. ^{[2
]}

Wassell, Ian J. ^{[1
]}

机构：

[1] Univ Cambridge, Comp Lab, Cambridge CB2 1TN, England

[2] Univ Porto, Inst Telecommun, Dept Ciencia Comp, Oporto, Portugal

来源：

2012 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) | 2012年

关键词：

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

Sparse signals can be sensed with a reduced number of random projections and then reconstructed if compressive sensing (CS) is employed. Traditionally, the projection matrix has been chosen as a random Gaussian matrix, but improved reconstruction performance can be obtained by optimizing the projection matrix. In this paper, we are interested in projection matrix designs for sensing sparse signals in overcomplete dictionaries. In particular, we put forth a closed form design that stems from the formulation of an optimization problem, which bypasses the complexity of iterative design approaches.

引用

页码：3457 / 3460

页数：4

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