A bidirectional associative memory based on optimal linear associative memory

1996 ◽  
Vol 45 (10) ◽  
pp. 1171-1179 ◽  
Author(s):  
Zheng-Ou Wang
Keyword(s):  
Associative Memory ◽  
Bidirectional Associative Memory ◽  
Optimal Linear

Mittag–Leffler synchronization for impulsive fractional-order bidirectional associative memory neural networks via optimal linear feedback control

2021 ◽  
Vol 26 (2) ◽  
pp. 207-226
Author(s):  
Jiazhe Lin ◽  
Rui Xu ◽  
Liangchen Li
Keyword(s):  
Neural Networks ◽  
Fractional Order ◽  
Associative Memory ◽  
Actuator Saturation ◽  
Sufficient Conditions ◽  
Linear Feedback ◽  
Impulsive Effect ◽  
Bidirectional Associative Memory ◽  
Optimal Linear ◽  
Predictor Corrector

In this paper, we are concerned with the synchronization scheme for fractional-order bidirectional associative memory (BAM) neural networks, where both synaptic transmission delay and impulsive effect are considered. By constructing Lyapunov functional, sufficient conditions are established to ensure the Mittag–Leffler synchronization. Based on Pontryagin’s maximum principle with delay, time-dependent control gains are obtained, which minimize the accumulative errors within the limitation of actuator saturation during the Mittag–Leffler synchronization. Numerical simulations are carried out to illustrate the feasibility and effectiveness of theoretical results with the help of the modified predictor-corrector algorithm and the forward-backward sweep method.

A Reconfigurable Bidirectional Associative Memory Network with Memristor Bridge

2021 ◽  
Author(s):  
Yingying Li ◽  
Junrui Li ◽  
Jie Li ◽  
Shukai Duan ◽  
Lidan Wang ◽  
...  
Keyword(s):  
Associative Memory ◽  
Bidirectional Associative Memory ◽  
Memory Network

New results on impulsive type inertial bidirectional associative memory neural networks

2020 ◽  
Vol 21 (2) ◽  
pp. 324-339 ◽  
Author(s):  
Chaouki Aouiti ◽  
Mahjouba Ben Rezeg ◽  
Yang Cao
Keyword(s):  
Neural Networks ◽  
Associative Memory ◽  
Bidirectional Associative Memory

Dynamics of fuzzy impulsive bidirectional associative memory neural networks with time-varying delays

2012 ◽  
Vol 40 (1-2) ◽  
pp. 289-317 ◽  
Author(s):  
R. Rakkiyappan ◽  
Xiaodi Li ◽  
Donal O’Regan
Keyword(s):  
Neural Networks ◽  
Associative Memory ◽  
Time Varying ◽  
Bidirectional Associative Memory

On exponential stability of bidirectional associative memory neural networks with time-varying delays

2009 ◽  
Vol 39 (3) ◽  
pp. 1083-1091 ◽  
Author(s):  
Ju H. Park ◽  
S.M. Lee ◽  
O.M. Kwon
Keyword(s):  
Neural Networks ◽  
Exponential Stability ◽  
Associative Memory ◽  
Time Varying ◽  
Bidirectional Associative Memory

Robust stability analysis for delayed Cohen-Grossberg-type bidirectional associative memory neural networks with norm-bounded uncertainties

2009 ◽  
Vol 223 (5) ◽  
pp. 693-707
Author(s):  
Y Wang ◽  
P Hu
Keyword(s):  
Neural Networks ◽  
Associative Memory ◽  
Robust Stability ◽  
Sufficient Conditions ◽  
Linear Matrix ◽  
Bidirectional Associative Memory ◽  
Parameter Uncertainties ◽  
Robust Stability Analysis ◽  
Global Robust Stability ◽  
Bounded Uncertainties

In this paper, the problem of global robust stability is discussed for uncertain Cohen-Grossberg-type (CG-type) bidirectional associative memory (BAM) neural networks (NNs) with delays. The parameter uncertainties are supposed to be norm bounded. The sufficient conditions for global robust stability are derived by employing a Lyapunov-Krasovskii functional. Based on these, the conditions ensuring global asymptotic stability without parameter uncertainties are established. All conditions are expressed in terms of linear matrix inequalities (LMIs). In addition, two examples are provided to illustrate the effectiveness of the results obtained.

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