Rathnakara.S; V.Udayashankara

Estimation of Noise in Nonstationary Signals Using Derivative of NLMS Algorithm

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Author(s)

Rathnakara.S ^1,* V.Udayashankara ¹

1. JSS Research Foundation, Mysore, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2017.08.02

Received: 16 Mar. 2017 / Revised: 16 Apr. 2017 / Accepted: 8 May 2017 / Published: 8 Aug. 2017

Index Terms

Speech enhancement, EEG, noise estimation, NLMS, EDNSS, EMSE

Abstract

In this paper a new Normalized Least mean square (NLMS) algorithm is proposed by modifying Error-data normalized step-size algorithm (EDNSS). The performance of proposed algorithm is tested for nonstationary signals like speech and Electroencephalogram (EEG). The simulations of above is carried by adding stationary and nonstationary Gaussian noise , with original speech taken from standard IEEE sentence (SP23) of NOIZEUS data base and EEG taken from EEG database (sccn.ucsd.edu). The output of proposed and EDNSS algorithm are measured with excess mean square error (EMSE) in both stationary and non stationary environment. The results can be appreciated that the proposed algorithm gives improved result over EDNSS algorithm and also the speed of convergence is maintained same as other NLMS algorithms.

Cite This Paper

Rathnakara.S, V.Udayashankara,"Estimation of Noise in Nonstationary Signals Using Derivative of NLMS Algorithm", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.9, No.8, pp.9-16, 2017. DOI: 10.5815/ijigsp.2017.08.02

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International Journal of Image, Graphics and Signal Processing (IJIGSP)