Synchronization for incommensurate Riemann–Liouville fractional competitive neural networks (CNN) with different time scales is investigated in this paper. Time delays and unknown parameters are concerned in the model, which is more practical. Two simple and effective controllers are proposed, respectively, such that synchronization between the salve system and the master system with known or unknown parameters can be achieved. The methods are more general and less conservative which can also be applied to commensurate integer-order systems and commensurate fractional systems. Furthermore, two numerical ensamples are provided to show the feasibility of the approach. Based on the chaotic masking method, the example of chaos synchronization application for secure communication is provided.
Synchronization for Incommensurate Riemann–Liouville Fractional-Order Time-Delayed Competitive Neural Networks With Different Time Scales and Known or Unknown Parameters1
Contributed by the Design Engineering Division of ASME for publication in the JOURNAL OF COMPUTATIONAL AND NONLINEAR DYNAMICS. Manuscript received September 7, 2018; final manuscript received December 26, 2018; published online February 15, 2019. Assoc. Editor: Dumitru Baleanu.
- Views Icon Views
- Share Icon Share
- Cite Icon Cite
- Search Site
Gu, Y., Wang, H., and Yu, Y. (February 15, 2019). "Synchronization for Incommensurate Riemann–Liouville Fractional-Order Time-Delayed Competitive Neural Networks With Different Time Scales and Known or Unknown Parameters." ASME. J. Comput. Nonlinear Dynam. May 2019; 14(5): 051002. https://doi.org/10.1115/1.4042494
Download citation file:
- Ris (Zotero)
- Reference Manager