scholarly journals Sampling-Based Event-Triggered Control for Neutral-Type Complex-Valued Neural Networks with Partly Unknown Markov Jump and Time-Varying Delay

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Zhen Wang ◽  
Lianglin Xiong ◽  
Haiyang Zhang ◽  
Yingying Liu
Keyword(s):  
Neural Networks ◽  
Neutral Type ◽  
Markov Jump ◽  
Stochastic Stabilization ◽  
Time Varying Delay ◽  
Type Complex ◽  
The Stability ◽  
First Time ◽  
Complex Valued ◽  
Event Triggered

This work is devoted to studying the stochastic stabilization of a class of neutral-type complex-valued neural networks (CVNNs) with partly unknown Markov jump. Firstly, in order to reduce the conservation of our stability conditions, two integral inequalities are generalized to the complex-valued domain. Secondly, a state-feedback controller is designed to investigate the stability of the neutral-type CVNNs with H ∞ performance, making the stability problem a further extension, and then, the stabilization of the CVNNs with H ∞ performance is investigated through a sampling-based event-triggered (SBET) control for the first time that the transmission event is not triggered except when it violates the event-triggered condition. Finally, two examples are given to illustrate the validity and correctness of our obtained theorems.

scholarly journals Stability Analysis of Quaternion-Valued Neutral-Type Neural Networks with Time-Varying Delay

Mathematics ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 101 ◽  
Author(s):  
Jinlong Shu ◽  
Lianglin Xiong ◽  
Tao Wu ◽  
Zixin Liu
Keyword(s):  
Neural Networks ◽  
Convex Combination ◽  
Neutral Type ◽  
Stability Conditions ◽  
Time Varying ◽  
Time Varying Delay ◽  
Convex Inequality ◽  
Inequality Technique ◽  
Combination Approach ◽  
Complex Valued

This paper addresses the problem of global μ -stability for quaternion-valued neutral-type neural networks (QVNTNNs) with time-varying delays. First, QVNTNNs are transformed into two complex-valued systems by using a transformation to reduce the complexity of the computation generated by the non-commutativity of quaternion multiplication. A new convex inequality in a complex field is introduced. In what follows, the condition for the existence and uniqueness of the equilibrium point is primarily obtained by the homeomorphism theory. Next, the global stability conditions of the complex-valued systems are provided by constructing a novel Lyapunov–Krasovskii functional, using an integral inequality technique, and reciprocal convex combination approach. The gained global μ -stability conditions can be divided into three different kinds of stability forms by varying the positive continuous function μ ( t ) . Finally, three reliable examples and a simulation are given to display the effectiveness of the proposed methods.

scholarly journals Global Exponential Stability of Periodic Solution for Neutral-Type Complex-Valued Neural Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Song Guo ◽  
Bo Du
Keyword(s):  
Neural Networks ◽  
Exponential Stability ◽  
Periodic Solutions ◽  
Global Exponential Stability ◽  
Neutral Type ◽  
Sufficient Conditions ◽  
Mawhin’S Continuation Theorem ◽  
Type Complex ◽  
Existence Of Periodic Solutions ◽  
Complex Valued

This paper deals with a class of neutral-type complex-valued neural networks with delays. By means of Mawhin’s continuation theorem, some criteria on existence of periodic solutions are established for the neutral-type complex-valued neural networks. By constructing an appropriate Lyapunov-Krasovskii functional, some sufficient conditions are derived for the global exponential stability of periodic solutions to the neutral-type complex-valued neural networks. Finally, numerical examples are given to show the effectiveness and merits of the present results.

scholarly journals Adaptive Event-Triggered Synchronization of Networked Neural Networks with Time-Varying Delay Subject to Actuator Saturation

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Yao Xu ◽  
Renren Wang ◽  
Hongqian Lu ◽  
Xingxing Song ◽  
Yahan Deng ◽  
...  
Keyword(s):  
Neural Networks ◽  
Actuator Saturation ◽  
Synchronization Error ◽  
Linear Matrix ◽  
Time Varying ◽  
Time Varying Delay ◽  
Network Utilization ◽  
The Stability ◽  
Varying Delay ◽  
Event Triggered

This paper discusses the adaptive event-triggered synchronization problem of a class of neural networks (NNs) with time-varying delay and actuator saturation. First, in view of the limited communication channel capacity of the network system and unnecessary data transmission in the NCSs, an adaptive event-triggered scheme (AETS) is introduced to reduce the network load and improve network utilization. Second, under the AETS, the synchronization error model of the delayed master-slave synchronization system is constructed with actuator saturation. Third, based on Lyapunov–Krasovskii functional (LKF), a new sufficient criterion to guarantee the asymptotic stability of the synchronization error system is derived. Moreover, by solving the stability criterion expressed in the form of a set of linear matrix inequalities (LMIs), some necessary parameters of the system are obtained. At last, two examples are expressed to demonstrate the feasibility of this method.

scholarly journals Improved Stability Criteria of Static Recurrent Neural Networks with a Time-Varying Delay

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Lei Ding ◽  
Hong-Bing Zeng ◽  
Wei Wang ◽  
Fei Yu
Keyword(s):  
Neural Networks ◽  
Recurrent Neural Networks ◽  
Linear Matrix ◽  
Time Varying ◽  
Time Varying Delay ◽  
Improved Stability ◽  
The Stability ◽  
Delay Dependent ◽  
Delay Dependent Stability ◽  
Varying Delay

This paper investigates the stability of static recurrent neural networks (SRNNs) with a time-varying delay. Based on the complete delay-decomposing approach and quadratic separation framework, a novel Lyapunov-Krasovskii functional is constructed. By employing a reciprocally convex technique to consider the relationship between the time-varying delay and its varying interval, some improved delay-dependent stability conditions are presented in terms of linear matrix inequalities (LMIs). Finally, a numerical example is provided to show the merits and the effectiveness of the proposed methods.

Sign in / Sign up

Export Citation Format

Share Document