Implementation of Adaptive Noise Canceller with Instantaneous Gain 


Vol. 34,  No. 8, pp. 756-763, Aug.  2009


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  Abstract

The Least Mean Square (LMS) algorithm is often used to restore signal corrupted by additive noise. A major defect of this algorithm is that the excess Mean Square Error (EMSE) increases linearly according to speech signal power. This result reduces the efficiency of performance significantly due to the large EMSE around the optimum value. Choosing a small step size solves this defect but causes a slow rate of convergence. The step size must be optimized to satisfy a fast rate of convergence and minimize EMSE. In this paper, the Instantaneous Gain Control (IGC) algorithm is proposed to deal with the situation as it exists in speech signals. Simulations were carried out using a real speech signal combined with Gaussian white noise. Results demonstrate the superiority of the proposed IGC algorithm over the LMS algorithm in rate of convergence, noise reduction and EMSE.

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  Cite this article

[IEEE Style]

J. Lee, C. Kim, C. Lee, "Implementation of Adaptive Noise Canceller with Instantaneous Gain," The Journal of Korean Institute of Communications and Information Sciences, vol. 34, no. 8, pp. 756-763, 2009. DOI: .

[ACM Style]

Jae-Kyun Lee, Chun-Sik Kim, and Chae-Wook Lee. 2009. Implementation of Adaptive Noise Canceller with Instantaneous Gain. The Journal of Korean Institute of Communications and Information Sciences, 34, 8, (2009), 756-763. DOI: .

[KICS Style]

Jae-Kyun Lee, Chun-Sik Kim, Chae-Wook Lee, "Implementation of Adaptive Noise Canceller with Instantaneous Gain," The Journal of Korean Institute of Communications and Information Sciences, vol. 34, no. 8, pp. 756-763, 8. 2009.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880