Filtered-X Adaptive Neuro-Fuzzy Inference Systems for Nonlinear Active Noise Control

  • Riyanto T. Bambang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4491)


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 performed 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.


Membership Function Fuzzy Inference System Firing Strength Secondary Path Active Noise Control 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Riyanto T. Bambang
    • 1
  1. 1.School of Electrical Engineering and Informatics, Bandung Institute of Technology, Jalan Ganesha 10, Bandung 40132Indonesia

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