Improved Results on Adaptive Control Approach for Projective Synchronization of Neural Networks with Time-Varying Delay

2019 ◽  
Vol 20 (6) ◽  
pp. 623-631 ◽  
Author(s):  
Abdujelil Abdurahman ◽  
Malika Sader ◽  
Haijun Jiang
Keyword(s):  
Neural Networks ◽  
Functional Method ◽  
Mean Value ◽  
Projective Synchronization ◽  
Mean Value Theorem ◽  
Time Varying ◽  
Chaotic Neural Networks ◽  
Control Approach ◽  
Time Varying Delay ◽  
Varying Delay

AbstractCompared to other types of synchronization such as complete synchronization and lag synchronization, there is a unique advantage in projective synchronization since it can greatly improve the security of communication. In this paper, the projective synchronization problem of a class of chaotic neural networks with time-varying delay is investigated via designing a novel adaptive controller. Some simple and useful criteria are derived by employing Lyapunov functional method and Lagrange mean value theorem. Finally, an example and its numerical simulations are given to demonstrate the effectiveness of the proposed control schemes. It is worth to mention that the designed controller in this paper dos not require any knowledge about the activation functions, which can be seen the main novelty of the paper.

scholarly journals Synchronization in Array of Coupled Neural Networks with Unbounded Distributed Delay and Limited Transmission Efficiency

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Xinsong Yang ◽  
Mengzhe Zhou ◽  
Jinde Cao
Keyword(s):  
Neural Networks ◽  
Distributed Delay ◽  
Transmission Efficiency ◽  
Functional Method ◽  
Linear Matrix ◽  
Time Varying ◽  
Coupled Neural Networks ◽  
Time Varying Delay ◽  
Unbounded Distributed Delays ◽  
Varying Delay

This paper investigates global synchronization in an array of coupled neural networks with time-varying delays and unbounded distributed delays. In the coupled neural networks, limited transmission efficiency between coupled nodes, which makes the model more practical, is considered. Based on a novel integral inequality and the Lyapunov functional method, sufficient synchronization criteria are derived. The derived synchronization criteria are formulated by linear matrix inequalities (LMIs) and can be easily verified by using Matlab LMI Toolbox. It is displayed that, when some of the transmission efficiencies are limited, the dynamics of the synchronized state are different from those of the isolated node. Furthermore, the transmission efficiency and inner coupling matrices between nodes play important roles in the final synchronized state. The derivative of the time-varying delay can be any given value, and the time-varying delay can be unbounded. The outer-coupling matrices can be symmetric or asymmetric. Numerical simulations are finally given to demonstrate the effectiveness of the theoretical results.

scholarly journals Projective synchronization analysis for BAM neural networks with time-varying delay via novel control

2021 ◽  
Vol 26 (1) ◽  
pp. 41-56
Author(s):  
Malika Sader ◽  
Fuyong Wang ◽  
Zhongxin Liu ◽  
Zhongxin Chen
Keyword(s):  
Neural Networks ◽  
Adaptive Controller ◽  
Projective Synchronization ◽  
Time Varying ◽  
Bam Neural Networks ◽  
Application Process ◽  
Time Varying Delay ◽  
Synchronization Problem ◽  
Varying Delay ◽  
Theoretical Results

In this paper, the projective synchronization of BAM neural networks with time-varying delays is studied. Firstly, a type of novel adaptive controller is introduced for the considered neural networks, which can achieve projective synchronization. Then, based on the adaptive controller, some novel and useful conditions are obtained to ensure the projective synchronization of considered neural networks. To our knowledge, different from other forms of synchronization, projective synchronization is more suitable to clearly represent the nonlinear systems’ fragile nature. Besides, we solve the projective synchronization problem between two different chaotic BAM neural networks, while most of the existing works only concerned with the projective synchronization chaotic systems with the same topologies. Compared with the controllers in previous papers, the designed controllers in this paper do not require any activation functions during the application process. Finally, an example is provided to show the effectiveness of the theoretical results.

MEAN VALUE EXPONENTIAL STABILITY OF STOCHASTIC REACTION–DIFFUSION GENERALIZED COHEN–GROSSBERG NEURAL NETWORKS WITH TIME-VARYING DELAY

2007 ◽  
Vol 17 (09) ◽  
pp. 3219-3227 ◽  
Author(s):  
LI WAN ◽  
QINGHUA ZHOU ◽  
JIANHUA SUN
Keyword(s):  
Neural Networks ◽  
Exponential Stability ◽  
Sufficient Conditions ◽  
Reaction Diffusion ◽  
Mean Value ◽  
Time Varying ◽  
Time Varying Delay ◽  
The Stability ◽  
Stochastic Reaction ◽  
Varying Delay

Stochastic effects on the stability property of reaction–diffusion generalized Cohen–Grossberg neural networks (GDCGNNs) with time-varying delay are considered. By skillfully constructing suitable Lyapunov functionals and employing the method of variational parameters, inequality technique and stochastic analysis, the delay independent and easily verifiable sufficient conditions to guarantee the mean-value exponential stability of an equilibrium solution associated with temporally uniform external inputs to the networks are obtained. One example is given to illustrate the theoretical results.

An Improved Block Cryptosystem Based on Iterating Delayed Chaotic Neural Networks

2013 ◽  
Vol 380-384 ◽  
pp. 2623-2628
Author(s):  
Xin Guo Zou
Keyword(s):  
Neural Networks ◽  
Block Cipher ◽  
Chaotic Map ◽  
Binary Sequences ◽  
Time Varying ◽  
Chosen Plaintext Attack ◽  
Chaotic Neural Networks ◽  
Time Varying Delay ◽  
Delayed Chaotic Neural Networks ◽  
Varying Delay

Recently, a large number of chaotic cryptosystems have been proposed, many of them fundamentally flawed by lack of robustness and security. In this paper, we point out the weakness of a very recent block cipher algorithm which is based on the chaotic Hopfield neural networks with time varying delay and give the improved scheme of it. We provide the chosen plaintext attack to recover the permuted plaintext string, and point out that the encryption speed is not fast enough. It is shown that the dependence on the key, but not on the plaintext, to generate binary sequences of iterating the chaotic map mechanism facilitates leakage of the information and vulnerable been attacked. Based on such a fact, we give the improved scheme to obtain higher security and faster speed.

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