Abstract
AbstractThis paper presents a framework of the digital generation of non-Gaussian spiky excitations. This study is focused on the random spikiness, featuring large excursions with considerable energy and monotonic (nonstochastic) variations in a local time history. A first-order non-Gaussian stochastic time series model and its spectral representation are employed for the local spiky features. The stochastic model generates not only autocorrelation properties but also a unique shape of peaks formed with random spikes and monotonic variations between spikes. The Fourier representation of the stochastic model enables an effective control of the peaks and provides a filtering operation for the local feature generation in the frame of stationary stochastic process. Several spectral models with stochastic or ensemble-averaged amplitudes and four added phase functions have been developed. Thus, the phase is different from the uncorrelated uniform phases in a conventional spectral method. The essential feature o...
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.