Fixed/predefined-time lag synchronization of complex-valued BAM neural networks with stochastic perturbations.

• The fixed/predefined-time lag synchronization issue of complex-valued BAM neural networks with stochastic effects is studied by utilizing the non-separation approach. • The designed controller does not contain a linear term − λ i e i (t) and is only composed of two nonlinear terms, which reduce the control cost and provide more accurate settling time estimations. • The feasibility of the proposed synchronization scheme is verified by two numerical examples and their MATLAB simulations. • Compared with the previous corresponding works, the complexity of analyzing the fixed/predefined-time synchronization behaviour of original complex-valued master-slave systems is reduced thanks to the simplicity of non-separation method. This paper studies the fixed-time and predefined-time lag synchronization of a class of complex-valued BAM neural networks with random disturbances. Firstly, based on the non-separation method, some basic properties of sign function in complex domain are introduced. Then, two simple complex-valued controllers are designed to achieve the fixed/predefined-time lag synchronization of considered stochastic systems. Compared with the results of existing works, the designed complex-valued controllers do not contain the linear term − λ i e i (t) , which makes the controller more simpler and efficient. Finally, two numerical examples are provided to verify the feasibility of our results through MATLAB simulation. [ABSTRACT FROM AUTHOR]