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논문검색

Performance Comparison of Different Variable Filters for Noise Cancellation in Real-Time Environment

초록

영어

Elimination of noise from the signal is the major task in signal processing applications. Wiener filter removes noise efficiently but it requires large number of computations and it was updated with speed issue with adaptive filter. Adaptive filter has several algorithms to remove noise from the signal. This paper performs cancellation of noise from the signal using wiener filter and adaptive filter algorithms namely LMS, NLMS and RLS algorithms in real time environment. All these methods are compared using several parameters like step size, mean and variance of noise, mean square error, signal to noise ratio, speed, no. of. Iterations etc. In the existence work, the authors have compared the performance of the wiener filter & LMS algorithm in real time environment with sinusoidal input. This paper is extended by comparing different adaptive filter algorithms with the input taken in real time environment. It is observed that RLS algorithm performs noise cancellation better than all other algorithms. But it has high degree of complexity & cost while NLMS algorithm has moderate speed of performance and it is quietly chosen for several applications.

목차

Abstract
 1. Introduction
 2. Objective
 3. Related Work
 4. Problem Statement
 5. Wiener Filter
 6. Adaptive Filtering
 7. Algorithms of Adaptive Filter
  7.1. Least Mean Square (LMS) Algorithm
  7.2. Normalized Least Mean Square (NLMS) Algorithm
  7.3. Recursive Least Square (RLS) Algorithm
 8. Simulation Results
 9. Conclusion and Future Work
 References

저자정보

  • B. Ananda Krishna Professor, Department of ECE, Sri Mittapalli College of Engineering, Tummalapalem, Guntur District, Andhra Pradesh, India, Email
  • G. V. P. Chandra Sekhar Yadav Assistant Professor, Department of ECE, DVR & Dr.HS MIC College of Technology, Kanchikacherla, Krishna District, Andhra Pradesh, India

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