Coexistence behavior of a double-MR-based cellular neural network system and its circuit implementation

A new tri-cellular neural network(CNN) system based on double memristors is constructed which used a hyperbolic tangent function instead of the conventional segmentation function in this paper. The multiple equilibrium points existing in the CNN system are analyzed. Through Lyapunov exponential spectrum, bifurcation diagram, phase diagram, SE complexity and digital circuit implementation, the rich and complex dynamical characteristics of the double-MR-based CNN system are presented. Interestingly, changing different parameters and initial values, the system has multiple coexisting attractors which include periodic-periodic attractors, periodic-chaotic attractors, and chaotic-chaotic attractors. Finally, a hardware circuit of the memristive cellular neural network is designed and built on the basis of a DSP platform to verify the implementability of the network model. The improved double-MR-based Cellular neural network system provides a theoretical foundation in other fields of application, especially for secure communications.

Automated summary

A new tri-cellular neural network system based on double memristors is constructed in this paper. Instead of the conventional segmentation function, a hyperbolic tangent function is used. The rich and complex dynamical characteristics of the system are presented through various analyses and experiments. The improved system provides a theoretical foundation in other fields of application, particularly for secure communications.