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  • 标题:Projection Matrix Design for Co-Sparse Analysis Model Based Compressive Sensing
  • 本地全文:下载
  • 作者:Endra Oey ; Dadang Gunawan ; Dodi Sudiana
  • 期刊名称:MATEC Web of Conferences
  • 电子版ISSN:2261-236X
  • 出版年度:2018
  • 卷号:159
  • DOI:10.1051/matecconf/201815901042
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:Co-sparse analysis model based-compressive sensing (CAMBCS) has gained attention in recent years as alternative to conventional sparse synthesis model based (SSMB)-CS. The equivalent operator as counterpart of the equivalent dictionary in the SSMB-CS is introduced in the CAMB-CS as the product of projection matrix and transpose of the analysis dictionary. This paper proposes an algorithm for designing suitable projection matrix for CAMB-CS by minimizing the mutual coherence of the equivalent operator based on equiangular tight frames design. The simulation results show that the CAMB-CS with the proposed projection matrix outperforms the SSMB-CS in terms of the signal quality reconstruction.
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