A NOVEL APPROACH TO CLASSIFY AND CONVERT 1D SIGNAL TO 2D GRAYSCALE IMAGE IMPLEMENTING SUPPORT VECTOR MACHINE AND EMPIRICAL MODE DECOMPOSITION ALGORITHM.

M Azad,F Khaled,Mi Pavel

doi:10.21474/ijar01/8331

Abstract

08Jan 2019 A NOVEL APPROACH TO CLASSIFY AND CONVERT 1D SIGNAL TO 2D GRAYSCALE IMAGE IMPLEMENTING SUPPORT VECTOR MACHINE AND EMPIRICAL MODE DECOMPOSITION ALGORITHM. M. Azad , F. Khaled and M.I. Pavel. Department of Computer Science and Engineering, BRAC University, Dhaka, Bangladesh.

Highlights

This paper represents a novel approach to transform one dimension (1D) signals into two dimension (2-D) grayscale image and a feature extraction process to extricate detail texture data of this 2D image to classify signals utilizing multi-class support vector machine
The esteem of tests is normalized based on the tests of the signals within the time space, and Empirical Mode Decomposition (EMD) is to distinguish the low frequency which fundamentally represents to noise and evacuate it from the image
Fractal Texture Investigation (SFTA) algorithm is used to extricate the feature vectors which are utilized for classifying the signals using multi-class support vector machine (SVM)