MODELING OF ENTROPY BEHAVIOR IN SPATIALLY INHOMOGENEOUS STATISTICAL SYSTEMS

Zarkova Elizaveta Mikhailovna

The paper considers the method of modelling entropy and information flows in spatially inhomogeneous statistical systems. It is shown that defects in the structure of models have a significant impact on the entropy of the system. The application of this modelling method to describe the processes occurring in stochastic neural networks is discussed. It shows how the ideas of criticality can serve as a foundation for the construction of computational systems.

Keywords:entropy, Monte Carlo method, critical behavior, defects, Ising model, neural networks.