Filtered-s Lyapunov algorithm for active control of nonlinear noise processes

Author

Zhao, Haiquan ; Zhang, Jiashu

Author_Institution

Key Lab. of Signal & Inf. Process. of Sichan Province, Southwest Jiaotong Univ., Chengdu

fYear

2008

Firstpage

311

Lastpage

314

Abstract

This paper presents a filtered-s Lyapunov algorithm for nonlinear active noise control (NANC) using the filter blank implementation based on functional link artificial neural network (FLANN) filter. First, a Lyapunov function of the tracking error is defined, and adaptive FLANN filter coefficients are then adaptive adjusted based Lyapunov stability theory so that the error converges to zero asymptotically. Analysis of theory and simulation results both show that it has fast error convergence and lower stable state error properties. Moreover, its stability is guaranteed by Lyapunov stability theory.

Keywords

Lyapunov methods; active noise control; channel bank filters; filtering theory; neural nets; nonlinear filters; stability; Lyapunov function; Lyapunov stability theory; active control; filter blank implementation; filtered-s Lyapunov algorithm; functional link artificial neural network filter; nonlinear active noise control; nonlinear noise processes; stable state error property; tracking error; Active noise reduction; Adaptive filters; Convergence; Finite impulse response filter; Information filtering; Information filters; Lyapunov method; Neural networks; Nonlinear distortion; Recurrent neural networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing, 2008. ICSP 2008. 9th International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-2178-7

Electronic_ISBN

978-1-4244-2179-4

Type

conf

DOI

10.1109/ICOSP.2008.4697133

Filename

4697133