Centralized and Decentralized Data-Sampling Principles for Outer-Synchronization of Fractional-Order Neural Networks
This paper aims to investigate the outer-synchronization of fractional-order neural networks. Using centralized and decentralized data-sampling principles and the theory of fractional differential equations, sufficient criteria about outer-synchronization of the controlled fractional-order neural ne...
Saved in:
Main Author: | Jin-E Zhang |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2017-01-01
|
Series: | Complexity |
Online Access: | http://dx.doi.org/10.1155/2017/6290646 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Projective Synchronization of Nonidentical Fractional-Order Memristive Neural Networks
by: Chong Chen, et al.
Published: (2019-01-01) -
Adaptive Fuzzy Synchronization of Fractional-Order Chaotic Neural Networks with Backlash-Like Hysteresis
by: Wenqing Fu, et al.
Published: (2018-01-01) -
Quasi-Synchronization of Nonidentical Fractional-Order Memristive Neural Networks via Impulsive Control
by: Ruihan Chen, et al.
Published: (2021-01-01) -
Generalized Outer Synchronization between Complex Networks with Unknown Parameters
by: Di Ning, et al.
Published: (2013-01-01) -
Finite-Time Projective Synchronization of Fractional-Order Memristive Neural Networks with Mixed Time-Varying Delays
by: Meng Hui, et al.
Published: (2020-01-01)