In this paper I describe an evolutionary wavelet network to optimize the filtering of a statistical time series into separate contributions. The wavelet base is regarded as a neural network where the network nodes are discrete wavelet transforms, the wavelon, and the network structure and parameters are selected through evolutionary techniques. With this combined approach I can separate stochas...

Artificial neural network (ANN) has application in communication engineering in diverse areas such as channel equalization, channel modeling, error control code because of its capability of nonlinear processing, adaptability, and parallel processing. On the other hand, wavelet transform (WT) with both the time and the frequency resolution provides the exact representation of signal in both doma...

The paper discusses the fast seismic performance assessment of structures using truncated pulse-like ground motion records. It is shown that it possible to truncate a signal novel wavelet-based definition identifies duration predominant velocity pulse. time-history still able efficiently reproduce increased demand near-field records typically produce. Substituting original with signal, can sign...

EMAT is used whenever a coupling medium like water shall be omitted. However, signal quality sometimes needs improvement, especially if surface quality of the product under test is poor. In this situation wall thickness measurements may be a challenging task. Signal filtering using wavelet based techniques proved to be suited well for improving SNR in situations with pulse-shaped signals. There...

A new facial biometric scheme is proposed in this paper. Three steps are included. First, a new nontensor product bivariate wavelet is utilized to get different facial frequency components. Then a modified 2D linear discriminant technique (M2DLD) is applied on these frequency components to enhance the discrimination of the facial features. Finally, support vector machine (SVM) is adopted for cl...

The standard methods for decomposition and analysis of evoked potentials are bandpass filtering, identification of peak amplitudes and latencies, and principal component analysis (PCA). We discuss the limitations of these and other approaches and introduce wavelet packet analysis. Then we propose the "single-channel wavelet packet model," a new approach in which a unique decomposition is achiev...