Finite-time Synchronization For Inertial Memristive Neural Networks

In this paper,the finite-time synchronization issues for inertial memristive neural networks will be investigated.By applying the stability theory and designing a suitable controller,constructing a useful Lyapunov function and applying appropriate inequality techniques,then,some new sufficient algebraic conditions will be obtained for ensuring the finite-time synchronization control.Meanwhile,we will give numerical examples to illustrate the effectiveness and feasibility by Mtalab.The whole paper consists of four chapters.Chapter 1 is introduction.Firstly,current situation of the development,characteristics and properties about memristive neural networks are introduced.Then,current situation of study on dynamic behavior of inertial neural networks is overviewed briefly.Finally,we combine inertial and memristive to discuss the synchronous control behavior for inertial memristive neural networks.In the second chapter,the problem of finite-time synchronization for inertial memristive neural networks was studied.We apply finite-time stable theory,construct suitable Lyapunov function and feedback control with term of sampled-date,then,combine inequality techniques,the sufficient conditions could be obtained for ensuring the finite-time synchronization control.Moreover,we discuss the estimated value of settling time in the different cases,and we can obtain the minimum estimated value of settling time.In the third chapter,the inertial memristive neural networks with mixed time-varying delay was researched,under a simple controller,by constructing suitable LyapunovKrasovskii functional and applying a new means,the sufficient conditions about finite-time synchronization and estimated value of settling time could be obtained.In the fourth chapter,we will summarize the whole work of the thesis and point out the developing directions that needs to be further explored in the future.