Nonlinear modelling of chaotic processes in systems and devices, including quantum electronics and photo may be based on the concept of compact geometric attractors. We present a new approach to analyze and predict the nonlinear dynamics of chaotic systems based on the concept of geometric attractors, chaos theory methods and algorithms for neural network simulation. Using information on the phase space evolution of the physical process in time and simulation of neural network modelling techniques can be considered as one of the fundamentally new approaches in the construction of global nonlinear models of the most effective and accurate description of the structure of the corresponding attractor.

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