Biorthogonal wavelet transform has been widely used in the fields of image denoising and image coding. It is usually realized by linear phase filters. All phase digital filter is a new type of linear phase digital filter which has been proposed in recent years and has frequency structure. On the basis of analyzing principle of biorthogonal wavelet transform and discrete cosine sequency filter (...

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...

The wavelet transform is a very useful tool for analyzing signals with self-similar behavior by virtue of the fact that the wavelet basis itself displays self similar properties. Recordings of mean arterial pressure in conscious dogs that had been shown to exhibit non-linear deterministic behaviour (self-similar characteristics) were used for analysis. We applied a redundant wavelet transform t...

Image fusion is processes of combining complementary information from a set of input images. The resultant fused image give large and reliable information. In this paper we study about Discrete wavelet and Discrete Multiwavelet and there use in image fusion. Discrete wavelet transform (DWT) technique is used for multi Resolution fusion. Multi Resolution fusion uses wavelet transform at multi sc...

In this paper we present our investigations on the potential of wavelet-based preprocessing for surface electromyographic speech recognition. We implemented several variants of the Discrete Wavelet Transform and applied them to electromyographical data. First we examined different transforms with various filters and decomposition levels and found that the Redundant Discrete Wavelet Transform pe...

The 2-band discrete wavelet transform (DWT) provides an octave-band analysis in the frequency domain, but this might not be ‘optimal’ for a given signal. The discrete wavelet packet transform (DWPT) provides a dictionary of bases over which one can search for an optimal representation (without constraining the analysis to an octave-band one) for the signal at hand. However, it is well known tha...