Artificial Immune Algorithm Based Signal Reconstruction for Compressive Sensing

摘要

The core of compressive sensing, i.e., signal reconstruction, is a constraint of signal sparsity problem, which can be implemented by ι _0 norm minimization. But ι_0 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 ι_0 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.