Adaptive nonlinear controller with integrated evaluation criterion for active noise attenuation

  • Xinghua Zhang*
  • , Xuemei Ren
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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 filtered-X gradient descent algorithm is developed to attenuate the nonlinear, non-Gaussian noises, which defines the weighted sum of Renyi's 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.

Original languageEnglish
Title of host publicationProceedings - 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009
Pages541-546
Number of pages6
DOIs
Publication statusPublished - 2009
Event2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009 - Shanghai, China
Duration: 20 Nov 200922 Nov 2009

Publication series

NameProceedings - 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009
Volume2

Conference

Conference2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009
Country/TerritoryChina
CityShanghai
Period20/11/0922/11/09

Keywords

  • Active noise control
  • Integrated evaluation criterion
  • Memory function mapping
  • Non-Gaussian noises
  • Renyi's quadratic error entropy

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