Filtered-X Adaptive Neuro-Fuzzy Inference Systems for nonlinear active noise control

被引：0
|
作者：
Bambang, Riyanto T. [1 ]
机构：
[1] Bandung Inst Technol, Sch Elect Engn & Informat, Bandung 40132, Indonesia
来源：
Advances in Neural Networks - ISNN 2007, Pt 1, Proceedings | 2007年 / 4491卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A new method for active noise control is proposed and experimentally demonstrated. The method is based on Adaptive Neuro-Fuzzy Inference Systems (ANFIS), which is introduced to overcome nonlinearity inherent in active noise control. A new algorithm referred to as Filtered-X ANFIS algorithm suitable for active noise control is proposed. Real-time experiment of Filtered-X ANFIS is per-formed using floating point Texas Instruments C6701 DSP. In contrast to previous work on ANC using computational intelligence approaches which concentrate on single channel and off-line adaptation, this research addresses multichannel and employs online adaptation, which is feasible due to the computing power of the DSP.
引用
收藏
页码：54 / 63
页数：10
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