| 引用本文: | 王春光,刘金江,孙即祥.基于粒子群优化的稀疏分解最优匹配原子搜索算法.[J].国防科技大学学报,2008,30(2):83-87.[点击复制] |
| WANG Chunguang,LIU Jinjiang,SUN Jixiang.Algorithm of Searching for the Best Matching Atoms Based on Particle Swarm Optimization in Sparse Decomposition[J].Journal of National University of Defense Technology,2008,30(2):83-87[点击复制] |
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| 基于粒子群优化的稀疏分解最优匹配原子搜索算法 |
| 王春光1, 刘金江2, 孙即祥1 |
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(1.国防科技大学 电子科学与工程学院，湖南 长沙 410073;2.南阳师范学院 计算机系，河南 南阳 473061)
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| 摘要: |
| 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。 |
| 关键词: 粒子群优化 稀疏分解 心电信号 图像处理 |
| DOI： |
| 投稿日期：2007-09-04 |
| 基金项目: |
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| Algorithm of Searching for the Best Matching Atoms Based on Particle Swarm Optimization in Sparse Decomposition |
| WANG Chunguang1, LIU Jinjiang2, SUN Jixiang1 |
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(1.College of Electronic Science and Engineering, National Univ. of Defense Technology, Changsha 410073, China;2.Department of Computer，Nanyang Normal University, Nanyang 473061，China)
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| Abstract: |
| 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 increase the efficiency processing signal using sparse decomposition, and then this method can meet (or near) the request of real time. Examinations have proved that this method is feasible. |
| Keywords: particle swarm optimization sparse decomposition ECG image processin |
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