Abstract
This paper discusses the synchronization of fractional order complex valued neural networks (FOCVNN) at the presence of time delay. Synchronization criterions are achieved through the employment of a linear feedback control and comparison theorem of fractional order linear systems with delay. Feasibility and effectiveness of the proposed system are validated through numerical simulations.
Highlights
Complex valued neural networks (CVNN) have attracted more attention in many research fields, such as signal processing, quantum waves, speech synthesis, and so on [1,2,3,4,5]
The main goal of this paper is to study the synchronization of fractional order complex valued neural networks (FOCVNN) with time delay by adopting a new strategy, and some interesting results are obtained
An error feedback controller is designed by using the comparison theorem of linear fractional order systems with delay and a fractional inequality
Summary
Complex valued neural networks (CVNN) have attracted more attention in many research fields, such as signal processing, quantum waves, speech synthesis, and so on [1,2,3,4,5]. It is worth pointing out that the interesting results of integer order CVNN can not be directly extended to fractional-order complex valued neural networks (FOCVNN). The stability and synchronization analysis of fractional order systems, including FOCVNN, are very difficult. Entropy 2018, 20, 54 to fractional order systems Taking these factors into consideration, many researchers have studied the dynamic behaviors of FOCVNN [20,21,22,23,24,25]. Stability analysis of fractional order complex valued neural networks and memristive neural networks with time delays were studied in [23,24]. Sufficient conditions are established by constructing a Lyapunov function, employing a fractional order inequality and comparison theorem of fractional order linear systems when there is a time delay
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