Non-Stationary Response of Stochastic Systems via Maximum Entropy Principle
Abstract
The principle of maximum entropy states that of all distributions (probability densities) that satisfy the appropriate moment constraints one should choose the distribution having the largest informational (Shannon) entropy. Since the entropy characterizes a global randomness of a random quantity in question, the principle of maximum entropy means that the maximum entropy distribution is maximally noncommittal with regard to the missing information. Due to this reason in statistics the maximum entropy distributions have been proposed to serve as the most unbiased prior distributions in Bayesian inferences. The principle has also been successfully applied in many other fields including reliability estimation of randomly vibrating systems. However, in all these studies the prior information was presented in the form of given (constant) moments.
Keywords
Maximum Entropy Stochastic System Moment Equation Maximum Entropy Method Maximum Entropy PrinciplePreview
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