Associative memory design using discrete-time second-order neural networks with local interconnections

1997 ◽  
Vol 44 (2) ◽  
pp. 153-158 ◽  
Author(s):  
M. Brucoli ◽  
L. Carnimeo ◽  
G. Grassi
Keyword(s):  
Neural Networks ◽  
Associative Memory ◽  
Discrete Time ◽  
Second Order ◽  
Memory Design

Multistability of discrete-time delayed Cohen–Grossberg neural networks with second-order synaptic connectivity

2015 ◽  
Vol 164 ◽  
pp. 252-261 ◽  
Author(s):  
Wu Yang ◽  
Yan-Wu Wang ◽  
Zhi-Gang Zeng ◽  
Ding-Fu Zheng
Keyword(s):  
Neural Networks ◽  
Discrete Time ◽  
Second Order ◽  
Synaptic Connectivity

scholarly journals Global Exponential Stability of Discrete-Time Multidirectional Associative Memory Neural Network with Variable Delays

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Min Wang ◽  
Tiejun Zhou ◽  
Xiaolan Zhang
Keyword(s):  
Neural Networks ◽  
Exponential Stability ◽  
Equilibrium Point ◽  
Associative Memory ◽  
Discrete Time ◽  
Global Exponential Stability ◽  
Sufficient Condition ◽  
Variable Delays ◽  
Exponentially Stable ◽  
Inequality Technique

A discrete-time multidirectional associative memory neural networks model with varying time delays is formulated by employing the semidiscretization method. A sufficient condition for the existence of an equilibrium point is given. By calculating difference and using inequality technique, a sufficient condition for the global exponential stability of the equilibrium point is obtained. The results are helpful to design global exponentially stable multidirectional associative memory neural networks. An example is given to illustrate the effectiveness of the results.

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