coherent WaveBurst (cWB) is a highly configurable pipeline designed to detect broad range of gravitational-wave (GW) transients in the data worldwide network GW detectors. The algorithmic core cWB time–frequency analysis with Wilson–Daubechies–Meyer wavelets aimed at identification events without prior knowledge signal waveform. has been active development since 2003 and it used analyze all sci...

Orthogonal compact-support Daubechies wavelets are employed as bases for both space and time variables in the solution of the time-dependent Schrodinger equation. Initial value conditions are enforced using special early-time wavelets analogous to edge wavelets used in boundary-value problems. It is shown that the quantum equations may be solved directly and accurately in the discrete wavelet r...

Uncompressed multimedia data occupy more storage space and very high data rates for transmission. Innovation is always under process to derive new high speed and efficient image compression methodologies. The main aim of this paper is to determine suitable wavelet for image compression using hybrid wavelet multi neural network architecture. A detailed comprehensive experimental analysis is carr...

This paper develops a new class of wavelets for which the classical Daubechies zero moment property has been relaxed. The advantages of relaxing higher order wavelet moment constraints is that within the framework of compact support and perfect reconstruction (orthogonal and biorthogonal) one can obtain wavelet basis with new and interesting approximation properties. This paper investigates a n...

Electrical signals recorded from muscles require processing before its use, so the modeling of these bioelectric signals is necessary. Wavelets are used for the processing of signals that are non-stationary and time varying. The surface Electromyogram signals were estimated with following steps, first, the obtained signal was decomposed using wavelet transform; then, decomposed coefficients wer...

This chapter takes up the design of discrete wavelet transforms based on oversampled filter banks. In this case the wavelets form an overcomplete basis, or frame. In particular, we consider the design of systems that are analogous to Daubechies’ orthonormal wavelets — that is, the design of minimal length wavelet filters satisfying certain polynomial properties, but now in the oversampled case....

This paper concentrates on a new procedure which experimentally recognises gears and bearings faults of a typical gearbox system using a least square support vector machine (LSSVM). Two wavelet selection criteria Maximum Energy to Shannon Entropy ratio and Maximum Relative Wavelet Energy are used and compared to select an appropriate wavelet for feature extraction. The fault diagnosis method co...