Chaos and asymptotical stability in discrete-time recurrent neural networks with generalized input-output function (Q1609628)
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scientific article; zbMATH DE number 1782078
| Language | Label | Description | Also known as |
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| English | Chaos and asymptotical stability in discrete-time recurrent neural networks with generalized input-output function |
scientific article; zbMATH DE number 1782078 |
Statements
Chaos and asymptotical stability in discrete-time recurrent neural networks with generalized input-output function (English)
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15 August 2002
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The conditions for asymptotic stability for the occurrance of bifurcations and finally for the appearance of chaotic behaviour beyond a threshold of \(\Delta t\) are analyzed and founded by means of a number of theorems in the case of discrete time recurrent neural networks with input-output functions in the form of a generalized sigmoid function. Limited numerical applications illustrate the theory.
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chaos
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asymptotic stability
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bifurcation
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neural network
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snap-back repeller
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numerical examples
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discrete time
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