Some Applications of the Difference Analysis for Stochastic Systems
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.