TY - JOUR AU - Hioual, Amel AU - Oussaeif, Taki Eddine PY - 2022/01/14 Y2 - 2024/03/29 TI - Stability analysis and synchronization of incommensurate fractional-order neural netwroks JF - Innovative Journal of Mathematics (IJM) JA - IJM VL - 1 IS - 1 SE - Articles DO - 10.55059/ijm.2022.1.1/7 UR - https://www.sigmawings.com/journals/index.php/IJM/article/view/7 SP - 110 - 123 AB - <pre>This paper develops a theoretical framework for analyzing the stability of nonlinear incommensurate fractional-<br>order neural networks. A necessary theorem for asymptotical stability is established using the characteristic <br>equation for a nonlinear fractional-order system, and how to employ this theorem in stabilization is also <br>presented. With the suitable control, the difficulties of stabilization and synchronization of fractional-order <br>chaotic incommensurate fractional-order neural networks may be readily overcome. Two numerical examples have been <br>shown to demonstrate how the established theory may be used to investigate stability and construct stabilization<br> controllers.</pre> ER -