DocumentCode :
2999292
Title :
Adaptive noise canceller based on PSO algorithm
Author :
Xia, Liu ; Hui, Gao ; Jinfeng, Liu
Author_Institution :
Sch. of Electr. & Inf. Eng., Daqing Pet. Inst., Daqing
fYear :
2008
fDate :
1-3 Sept. 2008
Firstpage :
1759
Lastpage :
1762
Abstract :
Adaptive noise cancellation technology is a very good signal processing technology, which can eliminate background noise effectively. In order to restrain the traditional adaptive canceller from trapping in local optimum, the improved PSO algorithm is leading into the mutation operator according to standard derivation of swarm fit value to inhibit local optimum, and design an adaptive noise canceller based on three-tier neural network trained by improving PSO algorithm. Theoretical analysis and computer simulations show that this system has better noise cancellation capability compared to the traditional adaptive noise canceller, and increase SNR. greatly.
Keywords :
adaptive filters; adaptive signal processing; learning (artificial intelligence); neural nets; particle swarm optimisation; signal denoising; adaptive filter; adaptive noise cancellation; particle swarm optimisation; signal processing technology; three-tier neural network; Automation; Background noise; Convergence; Genetic mutations; Neural networks; Noise cancellation; Particle swarm optimization; Petroleum; Signal processing algorithms; Signal to noise ratio; PSO; adaptive noise canceller; neural network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation and Logistics, 2008. ICAL 2008. IEEE International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-2502-0
Electronic_ISBN :
978-1-4244-2503-7
Type :
conf
DOI :
10.1109/ICAL.2008.4636441
Filename :
4636441
Link To Document :
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