Abstract
The dynamic properties of a class of neural networks (which includes the Hopfield model as a special case) are investigated by studying the qualitative behavior of equilibrium points. The results fall into one of two categories: results pertaining to analysis (e.g., stability properties of an equilibrium, asymptotic behavior of solutions, etc.) and results pertaining to synthesis (e.g. the design of a neural network with prespecified equilibrium points which are asymptotically stable). Most (but not all) of the results presented are global, and their applicability is demonstrated by an example.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Keywords
Artificial neural networkEquilibrium pointClass (philosophy)Stability (learning theory)Exponential stabilityComputer scienceCellular neural networkHopfield networkMathematicsApplied mathematicsArtificial intelligenceMathematical economicsMathematical optimizationMachine learningMathematical analysisNonlinear systemDifferential equation
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Publication Info
- Year
- 1988
- Type
- article
- Volume
- 35
- Issue
- 8
- Pages
- 976-986
- Citations
- 238
- Access
- Closed
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Cite This
Jian-Lei Li,
A.N. Michel,
Wolfgang Porod
(1988).
Qualitative analysis and synthesis of a class of neural networks.
IEEE Transactions on Circuits and Systems
, 35
(8)
, 976-986.
https://doi.org/10.1109/31.1844
Identifiers
- DOI
- 10.1109/31.1844