Performance analysis of industrial noise cancellation with pso based wiener filter using adaptive LMS & NLMS

Author

Lakshmikanth, S. ; Natraj, K.R. ; Rekha, K.R.

Author_Institution

Jain Univ., Bangalore, India

fYear

2014

fDate

3-5 April 2014

Firstpage

363

Lastpage

368

Abstract

Industrial noise is generated due to the number of sources that interferes with the signals. The source and weight of noise signals are hard to analyze hence a collective form of noise called Gaussian Noise is considered in this paper. This noise is collective form of noise signals that arise in industrial and transmission scales of signal processing. We have implemented wiener filter, least-mean-square algorithm, normalized LMS algorithm for denoising the noisy signals. In this paper we propose a particle swarm optimization (PSO) based wiener filter for enhancement of filtering. A comparative analysis is performed on these algorithms and generated the MSE and PSNR values of signals..

Keywords

Gaussian noise; Wiener filters; adaptive signal processing; least mean squares methods; particle swarm optimisation; signal denoising; Gaussian noise; MSE; PSNR values; PSO; Wiener filter; adaptive NLMS; filtering enhancement; industrial noise cancellation; industrial scales; least-mean-square algorithm; noise signals source; noise signals weight; noisy signals denoising; normalized LMS algorithm; particle swarm optimization; performance analysis; signal interference; signal processing; transmission scales; Adaptation models; Estimation; Filtering algorithms; Least squares approximations; PSNR; Wiener filters; Digital Signals; LMS; NLMS; PSO; Wiener filter;

fLanguage

English

Publisher

ieee

Conference_Titel

Communications and Signal Processing (ICCSP), 2014 International Conference on

Conference_Location

Melmaruvathur

Print_ISBN

978-1-4799-3357-0

Type

conf

DOI

10.1109/ICCSP.2014.6949863

Filename

6949863