Compressive Sparse Binary Signals Reconstruction Algorithm Using Simulated Annealing

Compressive Sensing method has been used in several applications specially for Image processing and wireless sensor network applications where Binary Compressive Sensing(BCS) is widely used. However, BCS reconstruction process is considered one of the most challenge in the most of applications. Therefore, this paper aims to address the mentioned problem by proposing Compressive Sparse Binary Signals Reconstruction Algorithm Using Simulated Annealing (CSBCSA). CSBCSA uses the advantage of Simulated Annealing algorithm in terms of finding the optimal solutions using lightweight computation and the advantage of the easy and fast implementation for the greedy algorithm to solve the reconstruction problem. This integration makes CSBCSA outperform the baseline reconstruction algorithm as shown in the simulation results section.

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