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Can I read A Novel Local Stochastic Linearization Method via Two Extremum Entropy Principles on EtoBox?
A Novel Local Stochastic Linearization Method via Two Extremum Entropy Principles by Giuseppe Ricciardi; Isaac Elishakoff is a Engineering article available to read on EtoBox.
What is A Novel Local Stochastic Linearization Method via Two Extremum Entropy Principles about?
The classical Gaussian stochastic linearization method for non-linear random vibration problems is reinterpreted on the basis of the maximum entropy principle. Starting from this theoretical result, the maximum entropy principle allows to formulate a local stochastic linearization method, based on the substitution of the original non-linear system by an equivalent locally linear one. The expressions of the equivalent coe cients are derived. The equivalence of this method with a non-Gaussian closure based on the maximum entropy method for stochastic dynamics is evidenced. In addition, an alternative stochastic linearization method is proposed, based on the minimum cross-entropy principle. Numerical applications show the superiority of the two proposed local stochastic linearization methods over the Gaussian one.
Who reads A Novel Local Stochastic Linearization Method via Two Extremum Entropy Principles?
It is typically read by researchers, students, and practitioners in Engineering.
- Author
- Giuseppe Ricciardi; Isaac Elishakoff
- Publisher
- Elsevier Science; Elsevier ; Elsevier Ltd.; Elsevier BV (ISSN 0020-7462)
- Published
- 2002
- Language
- EN
- Field
- Engineering (Physical Sciences)