in this paper, a fault diagnosis system based on discrete wavelet transform (dwt) and artificial neural networks (anns) is designed to diagnose different types of fault in gears. dwt is an advanced signal-processing technique for fault detection and identification. five features of wavelet transform rms, crest factor, kurtosis, standard deviation and skewness of discrete wavelet coefficients of...

Multiresolution analysis via decomposition into wavelets has been established as an important transform technique in signal processing. A wealth of results is available on this subject, and particutarly, the framework has been extended to treat "nite length sequences of size 2n (for positive integers n) over "nite "elds. The present paper extends this idea further to provide a framework for dea...

In this paper, an optimal control of quadratic performance index with nonlinear constrained is presented. The sine-cosine wavelet operational matrix of integration and product matrix are introduced and applied to reduce nonlinear differential equations to the nonlinear algebraic equations. Then, the Newton-Raphson method is used for solving these sets of algebraic equations. To present ability ...

AE (Acoustic Emission) testing is an important way in the NDT (Non Destructive Testing) field and wavelet analysis is demonstrated to be a promising method to process AE signal. A wavelet analysis module based on DSP (Digital Signal Processor) implementation is developed for AE testing system of the composite material to make the wavelet analysis system much more small and portable. The impleme...

Multiple Input Multiple output (MIMO) antennas can be combined with orthogonal frequency division multiplexing (OFDM) to ensure spatial diversity gain and/or to increase spectral efficiency. MIMO communication system with Alamouti methods can improve the bit error rate (BER) and signal to noise ratio (SNR) thus distortions are reduced for higher data rate. Conventionally OFDM is Fast Fourier Tr...

Discrete-time wavelet transform (DWT) is found to be better than other transforms in the time-varying system analysis, e.g. for time-varying parametric modelling [16], time-varying systems identification [17], time-varying parameter estimation [18] and time domain signal analysis [19]. In the literature the common method to analyze the time-varying system using discrete-time wavelet transform i...