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Hyperchaotic Non-homogeneous Neural Network

Nonlinear systems may present complex dynamical behaviors, the chaotic one being the most analyzed recently. The present paper presents an analog neural network built around hysteretic neurons. The larger order of the neural network and chaotic behavior of the neurons lead to hyperchaotic dynamics of the resulting system. Using different parameters for each neuron makes the network nonhomogeneous, reducing even more the possibility of identifying its behaviors. Simulation results confirm the complexity of the nonlinear dynamics of the neural network and highlight the system performance.