Dynamic behaviors of far and near memristive electromagnetic induction in spoon neural network.

Abstract

In this paper, a special spoon neural network is proposed, which is composed of four neurons with direct connection and indirect connection. On this basis, the far induction network and the near induction network (NINN) are constructed by using hyperbolic tangent memristors to explore the influence of electromagnetic induction between neurons at different positions on the dynamic behavior of attractors. NINN exhibits more complex attractor structures and wider chaotic parameters, and also displays a heterogeneous coexisting attractor of limit cycles and chaos under network parameter control. By varying the parameters, coexisting chaotic attractors can be synthesized into a double scrolls attractor, and their oscillation amplitude can be controlled without changing the chaotic characteristics. The type of attractors in human brain determines the clarity of memory. These complex dynamic behaviors demonstrate that near induction has a more pronounced effect on the forgetting and disappearance of memory compared to far induction. Finally, a circuit using switches to change the type of electromagnetic induction is constructed and the results are verified.