scholarly journals Fixed-Time Synchronization of Neural Networks Based on Quantized Intermittent Control for Image Protection

Mathematics ◽  
2021 ◽  
Vol 9 (23) ◽  
pp. 3086
Author(s):  
Wenqiang Yang ◽  
Li Xiao ◽  
Junjian Huang ◽  
Jinyue Yang
Keyword(s):  
Neural Networks ◽  
Finite Time ◽  
Time Synchronization ◽  
Initial Conditions ◽  
Fixed Time ◽  
Encryption Algorithm ◽  
Intermittent Control ◽  
Practical Application ◽  
Image Protection

This paper considers the fixed-time synchronization (FIXTS) of neural networks (NNs) by using quantized intermittent control (QIC). Based on QIC, a fixed-time controller is designed to ensure that the NNs achieve synchronization in finite time. With this controller, the settling time can be estimated regardless of initial conditions. After ensuring that the system has stabilized through this strategy, it is suitable for image protection given the behavior of the system. Meanwhile, the encryption effect of the image depends on the encryption algorithm, and the quality of the decrypted image depends on the synchronization error of NNs. The numerical results show that the designed controller is effective and validate the practical application of FIXTS of NNs in image protection.

scholarly journals Improved Results on Finite-Time Passivity and Synchronization Problem for Fractional-Order Memristor-Based Competitive Neural Networks: Interval Matrix Approach

2022 ◽  
Vol 6 (1) ◽  
pp. 36
Author(s):  
Pratap Anbalagan ◽  
Raja Ramachandran ◽  
Jehad Alzabut ◽  
Evren Hincal ◽  
Michal Niezabitowski
Keyword(s):  
Neural Networks ◽  
Fractional Order ◽  
Finite Time ◽  
Time Synchronization ◽  
Initial Conditions ◽  
Interval Matrix ◽  
Linear Matrix ◽  
Parameter Mismatch ◽  
Synchronization Problem ◽  
State Dependent

This research paper deals with the passivity and synchronization problem of fractional-order memristor-based competitive neural networks (FOMBCNNs) for the first time. Since the FOMBCNNs’ parameters are state-dependent, FOMBCNNs may exhibit unexpected parameter mismatch when different initial conditions are chosen. Therefore, the conventional robust control scheme cannot guarantee the synchronization of FOMBCNNs. Under the framework of the Filippov solution, the drive and response FOMBCNNs are first transformed into systems with interval parameters. Then, the new sufficient criteria are obtained by linear matrix inequalities (LMIs) to ensure the passivity in finite-time criteria for FOMBCNNs with mismatched switching jumps. Further, a feedback control law is designed to ensure the finite-time synchronization of FOMBCNNs. Finally, three numerical cases are given to illustrate the usefulness of our passivity and synchronization results.

Sign in / Sign up

Export Citation Format

Share Document