STOCHASTIC RUNAWAY OF DYNAMICAL SYSTEMS
It may happen that a Markovian process does not allow a stationary solution (e.g. the Wiener process). Usually, this is not easy to check. However, for a subclass of N-dimensional processes which can be described as stochastic dynamical systems, sufficient criteria can be given in a relatively simple form. As a by-product, it turns out that entropy diverges in the sense of growing uncertainty. The resulting asymptotic, complete flattening of the distribution function is called stochastic runaway. Examples such as reflection of a plane wave from a half space with random refraction index are treated and counter-examples are given.
Bibliographic Reference: PHYSICA, VOL. 136A (1986), PP. 393-416
Record Number: 1989124137800 / Last updated on: 1987-01-01
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