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Statistical inference for block sparsity of complex signals

Authors :
Wang, Jianfeng
Zhou, Zhiyong
Yu, Jun
Wang, Jianfeng
Zhou, Zhiyong
Yu, Jun
Publication Year :
2019

Abstract

Block sparsity is an important parameter in many algorithms to successfully recover block sparse signals under the framework of compressive sensing. However, it is often unknown and needs to beestimated. Recently there emerges a few research work about how to estimate block sparsity of real-valued signals, while there is, to the best of our knowledge, no investigation that has been conductedfor complex-valued signals. In this paper, we propose a new method to estimate the block sparsity of complex-valued signal. Its statistical properties are obtained and verified by simulations. In addition,we demonstrate the importance of accurately estimating the block sparsity in signal recovery through asensitivity analysis.

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1234635298
Document Type :
Electronic Resource