Title :
Weak signal detection based on a new matching pursuit method
Author :
Xu, Gang ; Gao, Jie
Author_Institution :
Dept. of Electr. & Electron. Eng., North China Electr. Power Univ., Beijing
Abstract :
In this paper, the theory of sparse decomposition is introduced to weak signal detection, and the improved matching pursuit (MP) 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.
Keywords :
interference (signal); particle swarm optimisation; search problems; signal detection; anti-interference process; matching pursuit method; particle swarm optimization algorithm; rapid noise restraint; searching efficiency; sparse decomposition theory; time-frequency atoms; weak signal detection; weak sine wave signal; Algorithm design and analysis; Cybernetics; Iterative algorithms; Machine learning; Machine learning algorithms; Matching pursuit algorithms; Signal analysis; Signal detection; Signal to noise ratio; Time frequency analysis; MP algorithm; PSO algorithm; Signal detection; Wavelet transformation;
Conference_Titel :
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-2095-7
Electronic_ISBN :
978-1-4244-2096-4
DOI :
10.1109/ICMLC.2008.4620557
