Modified Adaptive Filtering Algorithm for Noise Cancellation in Speech Signals
Adaptive filtering techniques are one of the important techniques used for noise cancellation in speech and biomedical signals. The Least Mean Squares (LMS) algorithm is one of the widely used algorithms in many adaptive signal processing environments. The adaptive filtering algorithm with averaging (AFA) algorithm is an improvement over the widely used Least Mean Squares (LMS) algorithm and has an improved performance. In this paper, we propose a modification in the AFA algorithm with improved performance for speech signal processing. The proposed modification was implemented in Matlab and was tested for noise cancellation in speech signals. The simulation results showed that modification has improved performance in terms of signal-to-noise ratio compared to the original adaptive filtering algorithm. Ill. 6, bibl. 8 (in English; summaries in English, Russian and Lithuanian).
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