Vol.4 No.11 (November 2014)
Matching Pursuit Based on PSO and Atomic Property
As sparse representation of signals has excellent characteristics, it has been applied in several fields of signal processing. But it has a large scale of computing, which hinders its application in practical signal processing. Particle swarm optimization is simple to be realized, and the searching result is good. In this paper, Matching Pursuit is used to realize sparse representation of signals, and particle swarm optimization is used to effectively search the best atom in the process of MP. According to the property of atoms, the improved algorithm is optimized. At last, the simulation results demonstrate the feasibility of the new algorithm.
钱 建 , 赵毅智 , 庄智威 (2014) 基于粒子群优化和原子特性的匹配追踪算法。 计算机科学与应用， 4， 282-287. doi: 10.12677/CSA.2014.411039
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