A fast nonlinear filtering algorithm is presented. This algorithm propagates the entire conditional probability functions recursively in a computationally efficient manner using the discrete wavelet transform. With the multiresolution analysis capability offered by the wavelet transform we can speed up the computation by ignoring the high-frequency details of the probability function up to a ce...

In this paper, for the first time, combination of these two concepts is used earthquake acceleration wave. For purpose, eight earthquakes from four different locations in world have been selected. Initially, each filtered up to 5 stages using a discrete wavelet transform. Due close approximation frequency content wave original earthquake, approximate subsequent calculations. next stage, spectru...

The low voltage level synchrophasor measurement data are investigated to estimate the damping ratio and to detect any oscillation mode using Fast Fourier Transform (FFT) and Continuous Wavelet Transform (CWT). Complex Morlet (CM) is selected as a mother wavelet function considering its ability to reveal time and frequency localization simultaneously. A Two Area Four Machine System (TAFMS) model...

The continuous wavelet transform is a new approach to the problem of time-frequency analysis of signals such as electroencephalogram (EEG) and is a promising method for EEG analysis. However, it requires a convolution integral in the time domain, so the amount of computation is enormous. In this paper, we propose a fast wavelet transform (FWT) that the corrected basic fast algorithm (CBFA) and ...

The difficulty of defecation seriously affects the quality life bedridden elderly. To solve problem that it is difficult to know time elderly, this paper proposed a human pre-defecation prediction method based on multi-domain features and improved support vector machine (SVM) using bowel sound as original signal. includes three stages: extraction, feature optimization, prediction. In stage stat...

The computation complexity dominates Continuous Wavelet Transform (CWT) and the low frequency resolution limit the Discrete Wavelet Transform (DWT). The degradation in frequency resolution in Discrete Wavelet Transform (DWT) is due to the fact, that, DWT decomposes only the approximation coefficients at each level. This detail is not enough to analyse the signal like knock in the engine. The ac...

We describe a new method of frequency-domain deconvolution when the kernel has no spectral inverse. Discrete frequency interpolation is used to aviod zero-valued frequency samples. The algorithm does not suuer from the spectral singularities of the original kernel, its complexity is proportional to the fast Fourier transform, and a comparative noise study showed improved performance relative to...

Spatio-temper-al data mining involves exti-acting and analyzing useful information embedded in a large spatio temporal database. Cluster analysis, one of the data mining techniques, provides the capabilip to investigate the spatio-temporal variation of data. Previous studies in cluster analysis indicate that the optimal number of clusters could be varied with the temporal scale of input data. T...

Recently the Wavelet Transform has gained a lot of popularity in the field of signal and image processing. This is due to its capability of providing both time and frequency information simultaneously, hence giving a timefrequency representation of the signal. The traditional Fourier Transform can only provide spectral information about a signal. Moreover, the Fourier method only works for stat...

A discrete wavelet transform (DWT) is any wavelet transform for which the wavelets are discretely sampled. As with other wavelet transforms, a key advantage it has over Fourier transforms is temporal resolution as it captures both frequency and location information. DWT filter provides a high compression ratio and image reconstruction quality so as to serve the end user requirements. Some other...