Sentence examples for by applying the wavelet from inspiring English sources

In this paper, an analytical approach for seismic ground motions is developed by applying the wavelet transform, which focuses on the energy input to the structure.

This learning method is proved to be effective by applying the wavelet radial basis function neural network in the classification of surface discharge fault data set.

The constraints on the PID gains are given from many fictitious data, which are obtained by applying the wavelet transform to a step response.

Mittal and Kumar [14] and El-Azab [15] have contrived Fisher's equation by applying the wavelet Galerkin method.

This is effectively performed by applying the wavelet transform, in particular the Haar wavelet, to a series of values.

The employed embedding domain is obtained by applying the wavelet transform to the just-noticeable difference (JND -scaled representation of the original HDR image.

By applying the wavelets, frequential analysis, rough sets and dynamic scaling in connection with simple neural network we obtained novel and reliable classifier architecture.

To guarantee the reversibility, invertible integer to integer wavelet transforms are used, by applying the Lazy wavelet and the lifting construction (finite length filter), to avoid loss of information through forward and inverse transform.

At first, instantaneous specific loudness time histories are calculated over 1 24 bark range by applying the analytic wavelet transform and Zwicker loudness transform to the recorded noise.

Soils Foundat 1992 32 2):35 44], and by applying the discrete wavelet transform to the system matrix of the iteration equation, we estimate unknown material parameters for the case in which the number of unknown parameters exceeds the observed data.

This method combines the inverse approach and the direct approach [1,2], and by applying the discrete wavelet transform to the system matrix of the iteration equation, we estimate unknown material parameters for the case in which the number of unknown parameters exceed the observed data.