Hysteretic chaotic neural network for crossbar switch problems
A hysteretic chaotic neural network is proposed to solve the crossbar switch problem effectively. The chaotic neural network structure with hysteresis and its set computation characteristics are carried out. The simulation results show that the theory is corrected by simulating the chaotic neural network with randomly generated neurons. The network architecture is applied to the crossbar switch problem, and the results of the computer simulation are given to illustrate the computational capability of the network architecture. The simulation results show that the chaotic neural network structure with hysteresis neurons is better than the previous network structure for the crossbar switch problem in terms of cost, time, and optimal solution rate.