title: Lag Synchronization of Switched Neural Networks via Neural Activation Function and Applications in Image Encryption.
abstract: This paper investigates the problem of global exponential lag synchronization of a class of switched neural networks with time-varying delays via neural activation function and applications in image encryption. The controller is dependent on the output of the system in the case of packed circuits, since it is hard to measure the inner state of the circuits. Thus, it is critical to design the controller based on the neuron activation function. Comparing the results, in this paper, with the existing ones shows that we improve and generalize the results derived in the previous literature. Several examples are also given to illustrate the effectiveness and potential applications in image encryption.
authors.forename: Shiping
authors.initials: S
authors.lastname: Wen
authors.forename: Zhigang
authors.initials: Z
authors.lastname: Zeng
authors.forename: Tingwen
authors.initials: T
authors.lastname: Huang
authors.forename: Qinggang
authors.initials: Q
authors.lastname: Meng
authors.forename: Wei
authors.initials: W
authors.lastname: Yao
mesh_terms: D000465:Algorithms; D003116:Color; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D015233:Models, Statistical; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology*; D017711:Nonlinear Dynamics