Abstract
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.
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Bambang, R.T. (2007). Filtered-X Adaptive Neuro-Fuzzy Inference Systems for Nonlinear Active Noise Control. In: Liu, D., Fei, S., Hou, ZG., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4491. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72383-7_8
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DOI: https://doi.org/10.1007/978-3-540-72383-7_8
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