Autors: Rijlaarsdam D.J., Mladenov, V. M.
Title: Synchronization of chaotic cellular neural networks based on Rössler cells
Keywords: Cellular neural networks; Chaos; Rössler dynamics; Synchroni

Abstract: Using and extending the approach in previous studies [2, 3] we demonstrate synchronization of two hyper chaotic cellular neural networks consisting of 25 cells governed by chaotic Rössler dynamics. We guarantee global asymptotic stability of the synchronization manifold by designing a nonlinear observer in such a way that the resulting error system is linear and time invariant. This linear error system is evaluated and a state feedback is designed to accomplish full state synchronization. Analytical as well as numerical simulation results are presented. © 2006 IEEE.



    8th Seminar on Neural Network Applications in Electrical Engineering, Neurel-2006 Proceedings, pp. 41-43, 2006, Serbia, Neurel, DOI 10.1109/NEUREL.2006.341171

    Цитирания (Citation/s):
    1. Akhmet, M., 2020. SICNN with Chaotic/Almost Periodic Postsynaptic Currents. In Almost Periodicity, Chaos, and Asymptotic Equivalence (pp. 265-307). Springer, Cham. - 2020 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science

    Вид: пленарен доклад в международен форум, публикация в реферирано издание, индексирана в Scopus и Web of Science