Simulation and Comparative Analysis of LMS and RLS Algorithms Using Real Time Speech Input Signal

α
Prof. Komal R
Prof. Komal R
σ
Prof. Komal R. Borisagar
Prof. Komal R. Borisagar
ρ
Dr. G.R.Kulkarni
Dr. G.R.Kulkarni
α Kadi Sarva Vishwavidyalaya

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Simulation and Comparative Analysis of LMS and RLS Algorithms Using Real Time Speech Input Signal

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Abstract

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.

References

7 Cites in Article
  1. E Eleftheriou,D Falconer (1986). Tracking properties and steady-state performance of RLS adaptive filter algorithms.
  2. S Haykin (1991). Adaptive Filter Theory.
  3. S Haykin,A Sayed,J Zeidler,P Yee,P Wei (1997). Adaptive tracking of linear time-variant systems by extended RLS algorithms.
  4. S Kuo,D Morgan (1999). Active Noise Control: a tutorial review.
  5. J Allen (1994). How do humans process and recognize speech?.
  6. W Harrison,J Lim,E Singer (1986). A new application of adaptive noise cancellation.
  7. S Sugiyama (1999). An adaptive noise canceller with low signal distortion for speech codes‖.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

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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v1.2

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October 11, 2010

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en
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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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Simulation and Comparative Analysis of LMS and RLS Algorithms Using Real Time Speech Input Signal

Prof. Komal R. Borisagar
Prof. Komal R. Borisagar
Dr. G.R.Kulkarni
Dr. G.R.Kulkarni

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