International Journal of Science, Engineering and Computer Technology

Suman ¹, Poonam Beniwal ¹

Affiliations
1 Department of ECE, OITM, Hisar. Haryana, IN

Abstract

Active Noise Control (ANC) involves an electro acoustic or electromechanical system that cancels the primary (unwanted) noise based on the principle of superposition. An anti-noise signal of equal amplitude and opposite phase is generated and combined with the primary noise, resulting in the cancellation of the noise. A fundamental problem to be considered in ANC systems is the requirement of highly precise control, temporal stability and reliability. To produce high degree of attenuation, the amplitude and phase of both the primary and the secondary noise must match with the close precision. The adaptive filters are used to control the noise and it has a linear input and output characteristic. If a transfer path of the noise has nonlinear characteristics it will be difficult for the filter to generate an optimal anti-noise. In this study, we propose a algorithm, delta rule algorithm which uses non linear output function. Delta rule is used for learning complex patterns in. Artificial Neural Networks. We have implemented the adaptive filters using Least Mean Square (LMS) algorithm, Recursive Least Square (RLS) algorithm and compared the results.

Keywords

ANC, LMS, RLS, Delta Rule, Error Signal, Neural Networks.

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Pankaj Gupta ¹, Poonam Beniwal ¹

Affiliations
1 Department of ECE, OITM, Hisar. Haryana, IN

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.

Keywords

Adaptive Filters, Adaptive Algorithm, RLS, LMS.

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