Fixed-time synchronization of coupled memristive neural networks with
multi-links and application in secure communication
Abstract
This paper is devoted to investigating the issues of fixed-time
synchronization of coupled memristive neural networks with multi-links
(MCMNN). Based on the fixed-time stability criterion and the upper bound
estimate formula for the settling time, we propose a secure
communication scheme. The network with multi-links performance and
coupled form increase the complexity of network topology and the
unstable of systems, which improve security of communication in the
aspect of encrypt the plaintext signal. We design a proper controller
and build the Lyapunov function, several effective conditions are
obtained to achieve the fixed-time synchronization of MCMNN. Moreover,
the settling times can be estimated for fixed-time synchronization
without depending on any initial values. Meanwhile, the plaintext
signals can be recovered according to the fixed-time stability theorem.
Finally, numerical simulations are given to verify the effectiveness of
the theoretical results in fixed-time synchronization of MCMNN, and an
example of a secure communication scheme is given to show the usability
and superiority based on fixed-time stability theorem.