Speech Enhancement using Combinational Adaptive LMS Algorithms
The key to successful adaptive signal processing understands the fundamental properties of adaptive algorithms like LMS. Adaptive filter is used for the cancellation of the noise component (in the Speech and acoustic signal processing )which is overlap with undesired signal in the same frequency ran...
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Veröffentlicht in: | International journal of advanced computer research 2015-03, Vol.5 (18), p.100-100 |
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description | The key to successful adaptive signal processing understands the fundamental properties of adaptive algorithms like LMS. Adaptive filter is used for the cancellation of the noise component (in the Speech and acoustic signal processing )which is overlap with undesired signal in the same frequency range, but fixed LMS algorithm produces minimum convergence rate and fixed steady state error. So the authors present design, implementation and performance of adaptive FIR filter, based on variations in LMS algorithm, which produces better convergence rate and minimum steady state error compare to fixed LMS, and they also obtains denoised signal at output, and also they propose to calculate SNR values of Adaptive Filter with LMS algorithms and comparison is made among the LMS algorithms. |
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source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
subjects | Adaptive algorithms Adaptive filters Algorithms Convergence Errors Mathematical analysis Signal processing Speech processing Steady state |
title | Speech Enhancement using Combinational Adaptive LMS Algorithms |
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