Stochastic Decomposition and Application to Probabilistic Dynamics
Publication: Journal of Engineering Mechanics
Volume 121, Issue 1
Abstract
The frequency-domain analysis concerning the response of nested-cascade multiple input/output systems requires computation of the cross-spectral density matrices that involve the input, intermediate, and output vectors. Clearly, as the number of nested systems increases, the order of the cross-spectral density matrix increases, demanding additional computational effort. This feature lessens the computational attractiveness of the frequency-domain analysis. A stochastic decomposition technique is developed that improves the efficiency of conventional frequency-domain analysis by eliminating the intermediate step of estimating cross-spectral density matrices. Central to this technique is the decomposition of a set of correlated random processes into a number of component random processes. Statistically, any two processes decomposed in this manner are either fully coherent or noncoherent. A random subprocess obtained from this decomposition is expressed in terms of a decomposed spectrum. A theoretical basis for this approach and computational procedures for carrying out such decompositions in probabilistic dynamics are presented.
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Information & Authors
Information
Published In
Journal of Engineering Mechanics
Volume 121 • Issue 1 • January 1995
Pages: 162 - 174
Copyright
Copyright © 1995 American Society of Civil Engineers.
History
Published online: Jan 1, 1995
Published in print: Jan 1995
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