Global Stability and Bifurcation in Delayed Bidirectional Associative Memory Neural Networks With an Arbitrary Number of Neurons
2017 ◽
Vol 139
(8)
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Keyword(s):
In this paper, delayed bidirectional associative memory (BAM) neural networks, which consist of one neuron in the X-layer and other neurons in the Y-layer, will be studied. Hopf bifurcation analysis of these systems will be discussed by proposing a general method. In fact, a general n-neuron BAM neural network model is considered, and the associated characteristic equation is studied by classification according to n. Here, n can be chosen arbitrarily. Moreover, we find an appropriate Lyapunov function that under a hypothesis, results in global stability. Numerical examples are also presented.
2005 ◽
Vol 15
(07)
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pp. 2145-2159
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2020 ◽
Vol 0
(0)
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2018 ◽
Vol 50
(1)
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pp. 851-885
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2006 ◽
pp. 273-278
Keyword(s):
2006 ◽
pp. 598-607
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2018 ◽
Vol 32
(24)
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pp. 1850287
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2018 ◽
Vol 149
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pp. 69-90
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2002 ◽
Vol 297
(3-4)
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pp. 182-190
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