Synchronization of Markovian Jump Neural Networks for Sampled Data
Control Systems With Additive Delay Components:Analysis of Image
Encryption Technique
Abstract
In an modern world, image encryption played an vital role to prevent our
data from illegal abuser entre. Based on this, in this paper the
Markovian jump neural networks for synchronization of sampled-data
control systems with two additive delay components are used on the
looped functional method and its direct application is applied in image
encryption. On the basis of generalized Lyapunov functional approach
involves the states information such as x(tk) and x(tk+1) with few slack
variables and a tuning parameter are introduced . Furthermore, the
sampled-data controller is designed to contain both the present and
delayed state information, thereby enhancing the control performance and
design flexibility. Finally by using the new technique, the several
examples are highlighted in the numerical section and also the
effectiveness of an image encryption is studied.