For seismic resistant design of critical structures, a dynamic analysis, based on either response spectrum or time history is frequently required. Due to the lack of recorded data and randomness of earthquake ground motion that might be experienced by the structure under probable future earthquakes, it is usually difficult to obtain recorded data which fit the necessary parameters (e.g. soil ty...

The recent development of wavelet analysis techniques has made it possible to represent the temporal variations of frequency content in an earthquake accelerogram elegantly. These techniques are more versatile than the other time-frequency localizing techniques due to their flexible time-frequency windowing feature. This development has led to the timeand frequency-based characterizations of gr...

The Hartley transform, a real-valued alternative to the complex Fourier transform, is presented as an efficient tool for the analysis and simulation of earthquake accelerograms. This paper is introduced a novel method based on discrete Hartley transform (DHT) and radial basis function (RBF) neural network for generation of artificial earthquake accelerograms from specific target spectrums. Acce...

Numerical analysis applied to the Beznar dam accelerograms (longitudinal and transversal components) shows that the Fourier amplítude spectrum is a good approxímatíon to the pseudo-velocíty spectra. Thís fact makes possible to use displacement ar velocíty seismograrns to generate acceleration of the ground in places where acceleration data are not avallable. Maximae accelerations determined nea...

The input motion for seismic analysis of building structures is generally specified in design codes in terms of response spectrum. Therefore, real or simulated time histories for ground motions whose response spectrum matches approximately the design spectrum is desired. Among the various techniques currently available for generating spectrum compatible time histories it is possible to distingu...

In this paper, we introduce a novel algorithm for morphing any accelerogram into a spectrum matching one. First, the seed time series is re-expressed as a discrete Volterra series. The first-order Volterra kernel is estimated by a multilevel wavelet decomposition using the stationary wavelet transform. Second, the higher-order Volterra kernels are estimated using a complete multinomial mixing o...