Artificial immune algorithm based signal reconstruction for compressive sensing

The core of compressive sensing, i.e., signal reconstruction, is a constraint of signal sparsity problem, which can be implemented by l
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norm minimization. But l
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norm minimization requires exhaustively listing all possibility of the original signals, which is an NP-hard problem to achieve difficultly by traditional algorithm.This paper proposes a signal reconstruction algorithm based on artificial immune algorithm, which can solve l
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norm minimization directly. It has been proved through numerical simulations that performance of signal reconstruction and photo-acoustic image reconstruction based on the proposed method is superior to that of OMP algorithm.