Title :
Efficient adaptive noise cancellation using genetic optimization
Author :
Gholami-Boroujeny, Shiva ; Eshghi, Mohammad
Author_Institution :
Electr. & Comput. Eng. Fac., Shahid Beheshti Univ., Tehran, Iran
Abstract :
In this paper, the use of the genetic algorithm in optimization of a nonlinear filter in adaptive noise cancellation (ANC) system is proposed. While the standard adaptive algorithms in nonlinear systems may converge to a local minimum, genetic algorithms (GAs) handle this problem efficiently. Computer simulations show that a superior performance is achieved using the proposed system with a not complex GA. A comparison of the proposed system with a popular ANC system also shows a high reduction of estimation error´s power.
Keywords :
adaptive filters; adaptive signal processing; genetic algorithms; nonlinear filters; signal denoising; adaptive noise cancellation; genetic algorithms; genetic optimization; nonlinear filter; Adaptive systems; Distortion measurement; Genetics; Noise cancellation; Noise measurement; Nonlinear filters; adaptive noise cancellation; genetic optimization; nonlinear filter;
Conference_Titel :
Signal Processing (ICSP), 2010 IEEE 10th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-5897-4
DOI :
10.1109/ICOSP.2010.5656134