Modeling the reachable sets for positive linear systems using self-regulating adaptive perceptron type neural networks

2002 ◽  
Author(s):  
V.G. Rumchev ◽  
R.W. Swiniarski
Keyword(s):  
Neural Networks ◽  
Linear Systems ◽  
Reachable Sets

SYNCHRONIZING HIGH DIMENSIONAL CHAOTIC SYSTEMS VIA EIGENVALUE PLACEMENT WITH APPLICATION TO CELLULAR NEURAL NETWORKS

1999 ◽  
Vol 09 (04) ◽  
pp. 705-711 ◽  
Author(s):  
GIUSEPPE GRASSI ◽  
SAVERIO MASCOLO
Keyword(s):  
Neural Networks ◽  
Numerical Simulations ◽  
Linear Systems ◽  
Chaotic Systems ◽  
Cellular Neural Networks ◽  
High Dimensional ◽  
Suggested Approach ◽  
Error Dynamics ◽  
Controllability Property

In this paper a method for synchronizing high dimensional chaotic systems is developed. The objective is to generate a linear error dynamics between the master and the slave systems, so that synchronization is achievable by exploiting the controllability property of linear systems. The suggested approach is applied to Cellular Neural Networks (CNNs), which can be considered as a tool for generating complex hyperchaotic behaviors. Numerical simulations are carried out for synchronizing CNNs constituted by Chua's circuits.

Neural networks based approach solving multi-linear systems withM-tensors

2019 ◽  
Vol 351 ◽  
pp. 33-42 ◽  
Author(s):  
Xuezhong Wang ◽  
Maolin Che ◽  
Yimin Wei
Keyword(s):  
Neural Networks ◽  
Linear Systems
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