Performance analysis and optimization of sensing matrix and reconstruction algorithm have become a hot research field in compressed sensing.Matching pursuit algorithm has a huge computational problem for sparse signal decomposition,so a hybrid intelligent algorithm of using alternately particle swarm optimization and Levenberg Marquardt has been put forth to find the best atom.Firstly,a group of optimal approximate solutions are obtained by the way of the particle swarm optimization.Taking these approximate solutions as the initial values,the particle swarm optimization and LM algorithm are alternately used until the satisfactory optimal solution is found at last.These findings indicate that the new algorithm overcomes premature convergence of particle swarm optimization,at the same time weakens its dependence on the initial conditions in the LM algorithm.It guarantees the speed and precision of the solving process.
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王菊,王朝晖,刘银.基于PSO和LM的信号稀疏分解快速算法[J].激光与红外,2012,42(2):227~230 WANG Ju, WANG Zhao-hui, LIU Yin. Fast algorithm of sparse signal decomposition based on PSO and LM[J]. LASER & INFRARED,2012,42(2):227~230