Active Noise Control using Bacterial Foraging Optimization Algorithm
This paper proposes a nonlinear ANC system in which a new evolutionary algorithm based on the foraging behavior of E. coli bacteria is used for adaptive nonlinear filter coefficients optimization, called BFA_ANC. While the standard LMS based nonlinear filters may converge to local minima, the evolutionary algorithms may handle this problem efficiently and converge to the global minima. In addition, this class of algorithms does not require the identification of the secondary paths. Computer simulations show the major improvements in final residual noise, as well as the processing time of the proposed ANC system in comparison to the other techniques in the literature.
active noise control evolutionary algorithm bacterial foraging optimization algorithm BFA_ANC
Shiva Gholami-Boroujeny Mohammad Eshghi
Electrical and Computer Engineering faculty, Shahid Beheshti University Tehran, Iran
国际会议
2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)
北京
英文
2592-2595
2010-08-24（万方平台首次上网日期，不代表论文的发表时间）