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Excellent design of Noise Reduction for Speech Signal Using Grazing Estimation of signal Method  


Abstract Category: Engineering
Course / Degree: PhD-ECE
Institution / University: Anna University, India
Published in: 2006


Thesis Abstract / Summary:

This thesis introduced a new design of noise reduction in the received speech signal using adaptive techniques. Adaptive systems are used well efficiently to reduce noise from the signals using interference cancellation techniques. But the interference cancellation technique is efficient only when there is a scope of obtaining noise, correlated to the corrupting noise, where it is used as reference signal. But when the signal is transmitted through the channel the noise that gets added in the channel is totally random; hence there is no means of creating a correlated noise at the receiving end. Only way possible is to somehow extract the noise from the received signal itself as only the received signal can give the information of the noise added to it. The new method is about generating such three correlated noises from the received signal only as the means. For this a new method is being proposed called Grazing estimation of the signal. This output is fed to the wavelet technique and compare existing methods by using MATLAB and DSP Processor simulation.


Thesis Keywords/Search Tags:
Active Noise Control, Filtered-X LMS algorithm, Grazing estimation signal, Minimum mean square, Pseudo Code, SNR, PSNR, Wavelet and Matlab 6

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Submission Details: Thesis Abstract submitted by Subramani Manikandan from India on 24-Nov-2006 12:27.
Abstract has been viewed 3273 times (since 7 Mar 2010).

Subramani Manikandan Contact Details: Email: smani5k@yahoo.com



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