Volume 14, number 1
 PDF Downloads: 1256

De-noising Electroence phalogram (EEG) Signal using iterative Clipping Algorithm

Padmesh Tripathi and Abul Hasan Siddiqi

Department of Mathematics, School of Engineering and Technology, Sharda University 32-34, Knowledge Park- III, Greater Noida, India-201306.

Corresponding Author E-mail: padmesh01@rediffmail.com

DOI : http://dx.doi.org/10.13005/bbra/2470

ABSTRACT: Signal de-noising has been a topic of great interest for a long period. EEG is used to detect the neurological diseases. In the process of EEG recording, signal is contaminated due to several factors. Hence, for analysis of EEG signal in order to detect the diseases, it is necessary that signal must be de-noised first. Here, de-noising of signal is expressed as an inverse problem with total variation. This is an optimization problem. The solution of this optimization problem is obtained by using the iterative clipping algorithm. In this article, iterative clipping algorithm is used for de-noising EEG signal. To measure the performance of method, signal to noise ratio(SNR) and root mean square error(RMSE) have been calculated.  It has been observed that the approach used here, works well in de-noising the EEG signal.

KEYWORDS: EEG; inverse problems; de-noising; total variation; iterative clipping algorithm

Download this article as: 
Copy the following to cite this article:

Tripathi P, Siddiqi A. H. De-noising Electroence phalogram (EEG) Signal using iterative Clipping Algorithm. Biosci Biotech Res Asia 2017;14(1).
Copy the following to cite this URL:

Tripathi P, Siddiqi A. H. De-noising Electroence phalogram (EEG) Signal using iterative Clipping Algorithm. Biosci Biotech Res Asia 2017;14(1). Available from: https://www.biotech-asia.org/?p=21910

[ HTML Full Text]

Back to TOC