Global exponential stability of Markovian jumping stochastic impulsive uncertain BAM neural networks with leakage, mixed time delays, and α-inverse Hölder activation functions

Advances in Difference Equations ◽

10.1186/s13662-018-1553-7 ◽

2018 ◽

Vol 2018 (1) ◽

Author(s):

C. Maharajan ◽

R. Raja ◽

Jinde Cao ◽

G. Ravi ◽

G. Rajchakit

Keyword(s):

Neural Networks ◽

Exponential Stability ◽

Time Delays ◽

Global Exponential Stability ◽

Bam Neural Networks ◽

Activation Functions ◽

Markovian Jumping ◽

Mixed Time Delays

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Stochastic global exponential stability for neutral-type impulsive neural networks with mixed time-delays and Markovian jumping parameters

Communications in Nonlinear Science and Numerical Simulation ◽

10.1016/j.cnsns.2010.12.027 ◽

2011 ◽

Vol 16 (9) ◽

pp. 3786-3791 ◽

Author(s):

Haibo Bao ◽

Jinde Cao

Keyword(s):

Neural Networks ◽

Exponential Stability ◽

Time Delays ◽

Global Exponential Stability ◽

Neutral Type ◽

Markovian Jumping Parameters ◽

Markovian Jumping ◽

Mixed Time Delays

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Global exponential stability of fuzzy logical BAM neural networks with Markovian jumping parameters

2011 Seventh International Conference on Natural Computation ◽

10.1109/icnc.2011.6022081 ◽

2011 ◽

Author(s):

Zhengfeng Zhang ◽

Wuneng Zhou ◽

Dongyi Yang

Keyword(s):

Neural Networks ◽

Exponential Stability ◽

Global Exponential Stability ◽

Bam Neural Networks ◽

Markovian Jumping Parameters ◽

Markovian Jumping ◽

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Global exponential stability of uncertain memristor-based recurrent neural networks with mixed time delays

International Journal of Machine Learning and Cybernetics ◽

10.1007/s13042-017-0759-4 ◽

2017 ◽

Vol 10 (4) ◽

pp. 743-755

Author(s):

Jianmin Wang ◽

Fengqiu Liu ◽

Sitian Qin

Keyword(s):

Neural Networks ◽

Exponential Stability ◽

Recurrent Neural Networks ◽

Time Delays ◽

Global Exponential Stability ◽

Mixed Time Delays

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Global exponential stability via inequality technique for inertial BAM neural networks with time delays

Neurocomputing ◽

10.1016/j.neucom.2014.10.072 ◽

2015 ◽

Vol 151 ◽

pp. 1316-1326 ◽

Author(s):

Zhengqiu Zhang ◽

Zhiyong Quan

Keyword(s):

Neural Networks ◽

Exponential Stability ◽

Time Delays ◽

Global Exponential Stability ◽

Bam Neural Networks ◽

Inequality Technique

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Global Exponential Stability of Memristive Complex-valued Neural Networks with Mixed Time Delays and Impulsive Effects

2019 6th International Conference on Information, Cybernetics, and Computational Social Systems (ICCSS) ◽

10.1109/iccss48103.2019.9115451 ◽

2019 ◽

Author(s):

Xuejun Wang

Keyword(s):

Neural Networks ◽

Exponential Stability ◽

Time Delays ◽

Global Exponential Stability ◽

Impulsive Effects ◽

Mixed Time Delays ◽

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Robust exponential stability analysis for interval Cohen–Grossberg type BAM neural networks with mixed time delays

International Journal of Machine Learning and Cybernetics ◽

10.1007/s13042-013-0186-0 ◽

2013 ◽

Vol 5 (1) ◽

pp. 23-38 ◽

Author(s):

Qingqing He ◽

Deyou Liu ◽

Huaiqin Wu ◽

Sanbo Ding

Keyword(s):

Neural Networks ◽

Stability Analysis ◽

Exponential Stability ◽

Time Delays ◽

Bam Neural Networks ◽

Robust Exponential Stability ◽

Mixed Time Delays

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Exponential stability in the mean square for stochastic neural networks with mixed time-delays and Markovian jumping parameters

Nonlinear Dynamics ◽

10.1007/s11071-008-9433-4 ◽

2008 ◽

Vol 57 (1-2) ◽

pp. 209-218 ◽

Author(s):

Guanjun Wang ◽

Jinde Cao ◽

Jinling Liang

Keyword(s):

Neural Networks ◽

Exponential Stability ◽

Time Delays ◽

Stochastic Neural Networks ◽

Mean Square ◽

Markovian Jumping Parameters ◽

Markovian Jumping ◽

Mixed Time Delays ◽

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Global exponential stability of neutral high-order stochastic Hopfield neural networks with Markovian jump parameters and mixed time delays

ISA Transactions ◽

10.1016/j.isatra.2013.07.016 ◽

2013 ◽

Vol 52 (6) ◽

pp. 759-767 ◽

Author(s):

Haiying Huang ◽

Qiaosheng Du ◽

Xibing Kang

Keyword(s):

Neural Networks ◽

Exponential Stability ◽

Time Delays ◽

Global Exponential Stability ◽

Hopfield Neural Networks ◽

Markovian Jump ◽

Markovian Jump Parameters ◽

Mixed Time Delays

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Impulsive Cohen–Grossberg BAM neural networks with mixed time-delays: An exponential stability analysis issue

Neurocomputing ◽

10.1016/j.neucom.2017.11.028 ◽

2018 ◽

Vol 275 ◽

pp. 2588-2602 ◽

Author(s):

C. Maharajan ◽

R. Raja ◽

Jinde Cao ◽

G. Rajchakit ◽

Ahmed Alsaedi

Keyword(s):

Neural Networks ◽

Stability Analysis ◽

Exponential Stability ◽

Time Delays ◽

Bam Neural Networks ◽

Mixed Time Delays

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Exponential Convergence Rate Estimation for a Class of BAM Neural Networks with Time-Delays

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.143-144.707 ◽

2010 ◽

Vol 143-144 ◽

pp. 707-711

Author(s):

Jian Dong Yu

Keyword(s):

Neural Networks ◽

Exponential Stability ◽

Time Delays ◽

Linear Matrix ◽

Bam Neural Networks ◽

Parameter Uncertainties ◽

Mixed Time Delays ◽

Weighting Matrix ◽

This paper is concerned with the exponential stability analysis problem for a class of neutral bidirectional associative memory (BAM) neural networks with parameter uncertainties and mixed time-delays where the parameter uncertainties are norm-bounded and the mixed time-delays involve discrete, distributed and neutral time-delays. By utilizing free-weighting matrix method and an appropriately constructed Lyapunov-Krasovskii Functional, some nove delay-dependent and decay-rate dependent exponential stability criteria are derived in the terms of linear matrix inequalities (LMIs). Meanwhile, the maximum allowable decay rate can be estimated based on the obtained results. Two numerical examples are presented to demonstrate the effectiveness of the proposed method.

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