基于粒子群优化的稀疏分解最优匹配原子搜索算法

Algorithm of Searching for the Best Matching Atoms Based on Particle Swarm Optimization in Sparse Decomposition

信号的稀疏分解能得到信号的稀疏表示形式,便于进一步处理,但其计算非常复杂,是一个NP问题。粒子群优化是群体智能优化算法,算法简单,易于实现,且搜索效果好。把粒子群优化算法用于稀疏分解的最优匹配原子的搜索,能降低稀疏分解复杂度,同时减少稀疏分解的超完备字典对存储空间的占用,以提高用稀疏分解理论进行信号处理的计算效率,满足或接近实时性的要求。实验证明,此方法切实可行。

Sparse decomposition of signal can get sparse representation of signal,and then next disposal can use this sparse representation expediently.But sparse decomposition is very complex(NP problem).Particle swarm optimization is a kind of optimization algorithm using colony aptitude.Its theory is simple to be realized,and the result of searching is good.To reduce complexity of sparse decomposition and space of memory,particle swarm optimization is used in searching the best atom.Particle swarm optimization can ...