Dynamical analysis and DSP implementation of 3D Hopfield neural network under dual memristive electromagnetic radiation

Abstract Numerous important biological neural activities, such as changes in their own firing patterns and information transmission between neurons, are affected to some extent by electromagnetic radiation in the external environment. To explore the impacts of two different external electromagnetic radiation stimulation on neuronal activities in a neural network, a 3D Hopfield neural network under dual memristive electromagnetic radiation (DMEMRHNN) is proposed in this paper. Firstly, two memristor models for simulating different external electromagnetic radiation are proposed and introduced into the 3D Hopfield neural network (HNN), thus constructing the DMEMRHNN. Then, the rich dynamical behavior changes of the DMEMRHNN under the influence of parameters such as electromagnetic radiation intensity are analyzed. At the same time, the coexisting attractors, state transition, and rare and interesting 4-symmetric remerging Feigenbaum tree phenomena are discovered. Finally, the simulation results of the DMEMRHNN on MATLAB are verified through DSP experimental platform.