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In practical application, the statistical characteristics of signal and noise are usually unknown or can’t have been learned so that we hardly design fix coefficient digital filter. In allusion to this problem, the theory of the adaptive filter and adaptive noise cancellation are researched deeply. According to the Least Mean Squares (LMS) and the Recursive Least Squares (RLS) algorithms realize the design and simulation of adaptive algorithms in noise canceling, and compare and analyze the result then prove the advantage and disadvantage of two algorithms .The adaptive filter with MATLAB are simulated and the results prove its performance is better than the use of a fixed filter designed by conventional methods.
Prof. Komal R. 1970. \u201cSimulation and Comparative Analysis of LMS and RLS Algorithms Using Real Time Speech Input Signal\u201d. Unknown Journal GJRE Volume 10 (GJRE Volume 10 Issue 5): .
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Total Score: 107
Country: India
Subject: Uncategorized
Authors: Prof. Komal R. Borisagar , Dr. G.R.Kulkarni (PhD/Dr. count: 1)
View Count (all-time): 78
Total Views (Real + Logic): 20328
Total Downloads (simulated): 11052
Publish Date: 1970 01, Thu
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In practical application, the statistical characteristics of signal and noise are usually unknown or can’t have been learned so that we hardly design fix coefficient digital filter. In allusion to this problem, the theory of the adaptive filter and adaptive noise cancellation are researched deeply. According to the Least Mean Squares (LMS) and the Recursive Least Squares (RLS) algorithms realize the design and simulation of adaptive algorithms in noise canceling, and compare and analyze the result then prove the advantage and disadvantage of two algorithms .The adaptive filter with MATLAB are simulated and the results prove its performance is better than the use of a fixed filter designed by conventional methods.
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