Synchronization of Markovian jump neural networks for sampled data control systems with additive delay components: Analysis of image encryption technique
M. Tamil Thendral, Thiruvannamalai Radhakrishnan Ganesh Babu, A. Chandrasekar, Yang Cao
Abstract
In an modern world, image encryption played an vital role to prevent our data from illegal abuser entrée. 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. Meanwhile, and denotes the information states with tuning parameter and a few slack variable which is introduced in the derived result. Furthermore, the sampled‐data controller is intended both the present and delayed state information, to enroll the control performance and 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.