Adaptive Nonlinear Controller with Integrated Evaluation Criterion for Active Noise Attenuation
A novel adaptive nonlinear controller is presented for nonlinear active noise control systems, which is expanded by memory function mapping on the basis of a single neuron structure, and a generalized filtercd-X gradient descent algorithm is developed to attenuate the nonlinear, non-Gaussian noises, which defines the weighted sum of Renyis quadratic error entropy and the mean square error as the integrated evaluation criterion. Parzen-window estimation method is utilized to estimate the probability density function in the proposed algorithm. In addition, the convergence of the proposed approach is analyzed. The overall scheme has a relative simple structure and less learning parameters, which can deal with nonlinear and non-Gaussian noises. The simulation results demonstrate the validity of the proposed method.
active noise control non-Gaussian noises memory function mapping Renyis quadratic error entropy integrated evaluation criterion
Xinghua Zhang Xuemei Ren
School of Automation Beijing Institute of Technology Beijing,China
国际会议
上海
英文
1444-1449
2009-11-20（万方平台首次上网日期，不代表论文的发表时间）