Two-cell cellular neural networks: generation of new hyperchaotic multiscroll attractors

In this paper the attention is focused on the complex dynamic phenomena generated by cellular neural networks (CNNs). By taking as basic cell Chua's circuit with sine-type nonlinearity, it is shown that a simple two-cell CNN is able to generate hyperchaotic behaviors. In particular, the paper shows that new multiscroll attractors can be obtained by modifying circuit parameters related to the cell nonlinearities. Finally, different examples are reported to illustrate the effectiveness and robustness of the proposed approach.