Wavelet packet decomposition is used to investigate the time-varying characteristics of clinical EEG signals. On the basis of the nonstationary nature of clinical EEG rhythms, wavelet packet analysis is employed for designing filters with different frequency characteristics to detect 4 kinds of EEG rhythms. The coefficients of wavelet transformation corresponding to the rhythms are used to form...

An accurate and computationally efficient means of classifying myoelectric signal (MES) patterns has been the subject of considerable research effort in recent years. Effective feature extraction is crucial to reliable classification and, in the quest to improve the accuracy of transient MES pattern classification, many forms of signal representation have been suggested. It is shown that featur...

An image compression algorithm exploiting the interband and intraband dependencies in a multiresolution decomposition structure is introduced. The transform coefficients, other than those which belong to the DC band, are adaptively scanned into two different 1-D arrays. These arrays are generated by using the observed statistical behavior of wavelet transform coefficients, in an effort to maxim...

In this article, we investigate the application of wavelet packet transform as a novel spectrum sensing approach. The main attraction for wavelet packets is the tradeoffs they offer in terms of satisfying various performance metrics such as frequency resolution, variance of the estimated power spectral density (PSD) and complexity. The results of the experiments show that the wavelet based appr...

A novel vowel feature extraction method via hybrid wavelet and linear prediction coding (LPC) is presented here. The proposed Arabic vowels recognition system is composed of very promising techniques; wavelet transform (WT) with linear prediction coding (LPC) for feature extraction and feed forward backpropagation neural network (FFBPNN) for classification. Trying to enhance the recognition pro...

Abstract— In our present work, we propose a nature inspired population based speech enhancement technique to find the dynamic threshold value using Teaching-Learning Based Optimization (TLBO) algorithm by using shift invariant property of dual tree complex wavelet transform (DT-CWT). The performance of these proposed methods are evaluated in terms of Perceptual Evaluation of Speech Quality (PES...

In this paper, an object-based embedded image coding algorithm based on context classification and quadtree ordering in wavelet packet domain (OB-CCAQO) is proposed. To match up well with the quadtree-based embedded coder, a new cost function for the best basis selection is adopted in SA-DWPT (shape adaptive discrete wavelet packet transform). The significance probability of wavelet coefficient...

AIT, Bangalore, India UVCE, Bangalore, India Corresponding Author: H. Umadevi ___________________________________________________________________________ Abstract OFDM is novel multicarrier modulation (MCM) technique. It has strong advantage of being a generic transmission scheme whose actual characteristics can be widely customized to fulfill several requirements and constraints of an advanced...

Recent studies suggest that multicarrier systems using wavelets outperform conventional OFDM systems using the FFT, in that they have well-contained side lobes, improved spectral efficiency and BER performance, and they do not require a cyclic prefix. Here we study the wavelet packet and discrete wavelet transforms, comparing the BER performance of wavelet transform-based multicarrier systems a...

A method for constructing spread spectrum sequences is presented. The method is based on a linear, orthogonal, symmetric transform, the Rudin-Shapiro transform (RST), which is in many respects quite similar to the Haar wavelet packet transform. The RST provides the means for generating large sets of spread spectrum signals. This presentation provides a simple definition of the symmetric RST tha...