Evaluation of Adaptive Noise Cancellation using various Algorithm Techniques

( Vol-1,Issue-2,May 2015 )

Author(s): Mr. Kulvinder Singh, Mr. Kapil Sachdeva

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Page No: 48-53
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Keywords:

Noise, Adaptive filter, Matlab software, LMS, RlS, Kalman algorithm.

Abstract:

Noise means any unwanted sound. In signal processing or computing noise can be considered as a random unwanted data or signal that does not have any meaning. It means that the noise is not being used to transmit with a signal, i.e. addition to the signal is called noise. Adaptive filter have the ability to adjust their impulse response to filter out the correlated signal in the input. They require little or no a priori knowledge of the signal and noise characteristics that is correlated in some sense to the signal to be estimated. Unlike Non-adaptive or fixed filters have static or fixed filter coefficients and are designed to have a frequency response chosen to alter the spectrum of the input signal in a desired manner. The adaptive algorithm generates this correction factor based on the two factor i.e. input signal and error signals (difference between output and the desired signal). In this paper we proposed LMS and RLS, kalman algorithms define three different coefficient update algorithms. And evaluating these three techniques & choose best one.

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