A class of fractional order neural network systems with sector dead zones for synchronization

Synchronization is examined for a class of fractional order neural network systems with sector dead zones and orders between 1 and 2. Through variable replacement, the synchronization problem for systems with orders in(1,2) is reformulated as one with orders in(0, 1). Unknown nonlinear functions within these networks are approximated using Lipschitz continuity conditions, converting them into known functions with a residual error. A synchronization controller is constructed to align the slave neural network with the master neural network. Convergence of the synchronization error system is assessed using the Lipschitz stability criterion. Simulation examples are provided,with graphical depictions of the master-slave neural network system and error system illustrating the method′ s performance.