WEAK SIGNAL DETECTION BASED ON A NEW MATCHING PURSUIT METHOD
In this paper, the theory of sparse decomposition is introduced to weak signal detection, and the improved Matching Pursuit (IMP) algorithm is studied to accomplish anti- interference process of some typical signals, such as a weak sine wave signal submerged in strong noise. Given that the traditional MP algorithm has a large number of calculations, the novel Particle Swarm Optimization (PSO) algorithm is used to improve the efficiency of searching for time-frequency atoms, thereby achieving high search efficiency of time-frequency atoms and rapid noise restraint. The results of experiments indicated that the improved algorithm can effectively increase the search speed by approximately 100 times and reduce the noises above Signal to Noise Ratio (SNR) -15.
MP algorithm PSO algorithm Signal detection Wavelet transformation
GANG XU JIE GAO
Department of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206,China
国际会议
2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)
昆明
英文
1036-1040
2008-07-12（万方平台首次上网日期，不代表论文的发表时间）