Based on wavelet packet decomposition and conditions of the support vector kernel function, a nonlinear wavelet basis is introduced to construct the kernel function of support vector machine (SVM). A tighten wavelet support vector machine (WSVM), which has strong generalization ability is also obtained. In this study, a novel damage classification method based on wavelet support vector machine ...

Context: Intelligent fault locating in transmission lines consists of three main steps: feature extraction, feature selection, and utilizing a learning tool. Objective: The main objective of this paper is to propose a systematic approach for intelligent fault locating in transmission lines. Method: This paper extracts a group of candidate features by applying a combination of the Wavelet Packet...

In this work we describe and analyze algorithms for 2-D wavelet packet decomposition for MIMD distributed memory architectures. We discuss two different approaches: On the one hand algorithms generating the entire wavelet packet subband structure (as required for adaptive applications), on the other hand algorithms generating the lowest subband level only (as required for numerical applications...

Among the most significant characteristics of human beings is their ability to feel emotions. In recent years, human-machine interface (HM) research has centered on ways empower classification Mainly, human-computer interaction (HCI) concentrates methods that enable computers reveal emotional states humans. this research, an emotion detection system based visual IAPPS pictures through EMOTIV EP...

in this paper, a block-based method in wavelet domain for sar image coding is presented based on the ezbc algorithm. to better preserve edges and textural structure in sar images, instead of using traditional dyadic wavelet transform, a packet wavelet is employed. to improve the efficiency of the ezbc algorithm for sar image coding, a modified version of this algorithm, is proposed. this modifi...

Wavelet transform has been extensively used in machine fault diagnosis and prognosis owing to its strength to deal with non-stationary signals. The existing Wavelet transform based schemes for fault diagnosis employ wavelet decomposition of the entire vibration frequency which not only involve huge computational overhead in extracting the features but also increases the dimensionality of the fe...

We give a brief review of some of the wavelet-based techniques currently available for the analysis of arbitrary-length discrete time series. We discuss the maximal overlap discrete wavelet packet transform (MODWPT), a non-decimated version of the usual discrete wavelet packet transform, and a special case, the maximal overlap discrete wavelet transform (MODWT). Using least-asymmetric or coifle...