The Discrete Wavelet Transform is the most powerful and new signal compression technique which uses multiresolution analysis for analyzing speech signal. Here we are doing parallel speech compression using two different wavelet transforms like Haar wavelets and Bi-orthogonal wavelet transformation (Bior). The resultant of components which are in high frequency bands are fusioned together and di...

This paper concerns the issue of wavelet analysis of signals by continuous and discrete wavelet transforms (CWT – Continous Wavelet Transform, DWT – Discrete Wavelet Transform). The main goal of our work was to develop a program which, through the CWT and the DWT analyses, would obtain graph of time-scale changes and would transform it into the spectrum, that is a graph of frequency changes. In...

Estimation of fundamental frequency component of current and / or voltage signals is essential for relaying decision in most of the numerical algorithms used for the protection of power system components. Modern numerical relays generally use discrete Fourier transform for extracting the fundamental component from the post fault signals consisting of fundamental as well as non-fundamental frequ...

The wavelet transform is denoted by ‘WT’ gained wide-ranging approval in processing signal and in compressing image. A 2D analysis must be implemented to use WT for processing the image. Such powerful signal analysis technique can be implemented for non-stationary data using Lifting architecture for the Discrete Wavelet Transform (DWT). Since high speed implementation with low latency is a dema...

In this paper, a new scheme for recognition of isolated words in kannada Language speech, based on the Discrete Wavelet Transform(DWT) and PCA has been proposed. First, the DWT of the speech is computed and then MFCC coefficients are calculated. For this, Principal Component Analysis procedure is applied for speech recognition. This paper also presents the comparative results with respect to th...

In their recent paper, Alnasser and Foroosh derive a wavelet-domain (in-band) method for phase-shifting of 2-D "nonseparable" Haar transform coefficients. Their approach is parametrical to the (a priori known) image translation. In this correspondence, we show that the utilized transform is in fact the separable Haar discrete wavelet transform (DWT). As such, wavelet-domain phase shifting can b...

The wavelet transform is one of the important methods that are used to minimize noises and to analyze signals. The choice of wavelet and its associated scaling function are very important to obtain the most useful wavelet transforms. In the present work, it was investigated that the easy obtaining of the P and S phases by minimizing the noise at the three-component seismograms displacement reco...

Objective of this paper is to identify a person taking fingerprint as a biometric parameter using wavelet packet transform. Here both conventional discrete wavelet transform (DWT) and discrete wavelet packet transform (WPT) are used considering special basis function/matrix to extract the coefficients of basis functions those convey the most of the energy of the signal or image. Here top 5% coe...

Power system signals are associated with different types of abnormalities, which degrade efficiency of equipments and renders in their erratic operation. One of the causes of power quality degradation is unbalance in supply, which deteriorates the performance of induction motors, which is seen to be the most suitable drive for industrial applications. The objective of this work is to diagnose t...