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Multi-Frequency Noise Removal Based on Reinforcement Learning

In this paper, a neuro-fuzzy system is proposed to remove multifrequency noise from audio signals. There are two major elements in our method. The first comprises a fuzzy cerebellar model articulation controller (FCMAC) that is used to quantize the signals. The second one is developed based on the theory of stochastic real values (SRV) that is used to search the optimal frequencies for the overall trained system. We present a DSP implementation of the SRV algorithm and results on its performance in removing spectral noise that is buried in audio signals.

Authors: Lin, Ching-Shun; Kyriakakis, Chris
Affiliation: Immersive Audio Laboratory, Integrated Media Systems Center, Univ. of Southern California, Los Angeles, CA
AES Convention:115 (October 2003) Paper Number:5966 Import into BibTeX
Subject:Archiving and Restoration

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E-Library Location: (CD aes20)   /pp2003/pp0310/00085.pdf

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