Some Applications of the Difference Analysis for Stochastic Systems
Abstract
The work relates to a new way for analysis of one-dimensional stochastic systems, based on consideration of its higher order difference structure. From this point of view, the deterministic and random processes are analyzed. A new numerical characteristic for one-dimensional stochastic systems is introduced. The applications to single neuron models and neural networks are given.
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