Synchronization stability on the BAM neural networks with mixed time delays
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Ahmadjan Muhammadhaji
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Zhidong Teng
Abstract
This article investigates the general decay synchronization (GDS) for the bidirectional associative memory neural networks (BAMNNs). Compared with previous research results, both time-varying delays and distributed time delays are taken into consideration. By using Lyapunov method and using useful inequality techniques, some sufficient conditions on the GDS for BAMNNs are derived. Finally, a numerical example is also carried out to validate the practicability and feasibility of our proposed results. It is worth pointing out that the GDS may be specialized as exponential synchronization, polynomial synchronization and logarithmic synchronization. Besides, we can estimate the convergence rate of the synchronization by GDS. The obtained results in this article can be seen as the improvement and extension of the previously known works.
Funding source: National Natural Science Foundation of China
Award Identifier / Grant number: 11702237, 11861063
Acknowledgments
This work was supported by the National Natural Science Foundation of China [grant number 11702237], [grant number 11861063].
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Author contribution: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
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Research funding: This work was supported by the National Natural Science Foundation of China (grant number 11702237, 11861063).
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Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
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© 2020 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- Original Research Articles
- Stability control of a novel multidimensional fractional-order financial system with time‐delay via impulse control
- Periodic solutions for stochastic Cohen–Grossberg neural networks with time-varying delays
- The monotone iterative method for the integral boundary value problems of fractional p-Laplacian equations with delay
- Solvability of fractional differential inclusions with nonlocal initial conditions via resolvent family of operators
- Synchronization of Cohen-Grossberg fuzzy cellular neural networks with time-varying delays
- Application of Hermite–Padé approximation for detecting singularities of some boundary value problems
- The extended auxiliary equation mapping method to determine novel exact solitary wave solutions of the nonlinear fractional PDEs
- A numerical technique for a general form of nonlinear fractional-order differential equations with the linear functional argument
- Using the generalized Adams-Bashforth-Moulton method for obtaining the numerical solution of some variable-order fractional dynamical models
- Synchronization stability on the BAM neural networks with mixed time delays
- Nonlinear solution of the reaction–diffusion equation using a two-step third–fourth-derivative block method
Artikel in diesem Heft
- Frontmatter
- Original Research Articles
- Stability control of a novel multidimensional fractional-order financial system with time‐delay via impulse control
- Periodic solutions for stochastic Cohen–Grossberg neural networks with time-varying delays
- The monotone iterative method for the integral boundary value problems of fractional p-Laplacian equations with delay
- Solvability of fractional differential inclusions with nonlocal initial conditions via resolvent family of operators
- Synchronization of Cohen-Grossberg fuzzy cellular neural networks with time-varying delays
- Application of Hermite–Padé approximation for detecting singularities of some boundary value problems
- The extended auxiliary equation mapping method to determine novel exact solitary wave solutions of the nonlinear fractional PDEs
- A numerical technique for a general form of nonlinear fractional-order differential equations with the linear functional argument
- Using the generalized Adams-Bashforth-Moulton method for obtaining the numerical solution of some variable-order fractional dynamical models
- Synchronization stability on the BAM neural networks with mixed time delays
- Nonlinear solution of the reaction–diffusion equation using a two-step third–fourth-derivative block method
