基于Kasami码的聚类结构稀疏信号确定性感知矩阵

Hamid Nouasria, Mohamed Et-tolba
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引用次数: 1

摘要

聚类结构压缩感知是处理聚类结构稀疏信号的压缩感知的一个新方向。本文提出了一种基于Kasami码的CSS信号感知矩阵。Kasami规范已经成为几个建筑的主题。我们的想法是使这些结构适合CSS信号。所提出的矩阵赋予了聚类更多的意图。仿真结果表明了该矩阵的优越性能。因此,它提供了最高的精确回收率。此外,我们的矩阵的确定性方面使其更适合在硬件上实现。
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A Novel Deterministic Sensing Matrix Based on Kasami Codes for Cluster Structured Sparse Signals
Cluster structured compressive sensing is a new direction of compressive sensing, dealing with cluster structured sparse signals. In this paper, we propose a sensing matrix based on Kasami codes for CSS signals. The Kasami codes have been the subject of several constructions. Our idea is to make these constructions suitable to CSS signals. The proposed matrix, gives more intention to the clusters. Simulation results show the superior performance of our matrix. In that, it gives the highest rate of exact recovery. Moreover, the deterministic aspect of our matrix makes it more suitable to be implemented on hardware.
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