Earthquake force, loading more than structural capacity, cracking, material fatigue and the other unpredicted events were undeniable in the structure life cycle in order that environmental conditions of the structure would be changed and treats health. Damage of structures such as crack, corrosion of the post tension cables from inappropriate grouting of the post tension structures and etc. can...

In this study, the effect of earthquake frequency content and noise effects on damage detection has been investigated. For this purpose, the damage was defined as nonlinear behavior of beams and columns, and several ground motion records were scaled so that some elements yield under the applied excitation. Then the acceleration response data of each floor obtained using the nonlinear dynamic an...

A main feature of wavelet analysis is localizable characteristic in time-domain and frequency-domain. However, localizable characteristic is formed from time-frequency windows with elasticity. Sampling interval of wavelet transform can be automatically adjusted in the second wavelet sampling, therefore wavelet transform can focus to arbitrary details of observed signal. Sample is the important ...

Influence of weather variables on occurrence spiders in pigeon pea across locations seven agro-climatic zones India was studied addition to development forecast models with their comparisons performance. Considering the non-normal and nonlinear nature time series data spiders, non-parametric techniques were applied developed algorithm based combinations wavelet–regression wavelet–artificial neu...

Bayesian wavelet shrinkage methods are defined through a prior distribution on the space of wavelet coefficients after a Discrete Wavelet Transformation has been applied to the data. Posterior summaries of the wavelet coefficients establish a Bayes shrinkage rule. After the Bayes shrinkage is performed, an Inverse Discrete Wavelet Transformation can be used to recover the signal that generated ...

In this paper the use of classical and lifting based wavelets for image compression was presented. Both classical and lifting based wavelets are considered. Classical wavelets considered in this work are Haar wavelet, Daubechie wavelet, Coiflet wavelet, Biorthognal wavelet, Demeyer wavelet, and Symlet wavelet. Lifting based wavelet transforms considered are (5,3) and (9,7). Large number of imag...

The presence of a high level of noise is a characteristic in some tomographic imaging techniques such as positron emission tomography. Wavelet methods can smooth out noise while preserving signiicant features of images. Mallat et al. proposed a wavelet-based denoising scheme exploiting wavelet modulus maxima, but the scheme is sensitive to noise. In this study, we explore the properties of wave...

In this paper we present a new form of wavelet transform. Unlike the continuous wavelet transform (CWT) or discrete wavelet transform (DWT), the mother wavelet is chosen to be a discrete-time signal and wavelet coefficients are computed by correlating a given discrete-time signal with continuous dilations of the mother wavelet. The results developed are based on the definition of a discrete-tim...

Recently discrete wavelet transform and wavelet packet has emerged as popular techniques for image compression. The wavelet transform is one of the major processing components of image compression. The results of the compression change as per the basis and tap of the wavelet used. This paper compares compression performance of Daubechies, Biorthogonal, Coiflets and other wavelets along with res...