Publication | Closed Access
Necessary and sufficient condition for absolute stability of neural networks
204
Citations
17
References
1994
Year
Circuit ComplexityEngineeringNegative SemidefinitenessHopfield TypeSufficient ConditionMathematical FoundationsNeuronal NetworkSystem StabilitySemi-definite OptimizationNumerical StabilitySemidefinite ProgrammingLyapunov AnalysisStability AnalysisStability
The main result in this paper is that for a neural circuit of the Hopfield type with a symmetric connection matrix T, the negative semidefiniteness of T is a necessary and sufficient condition for Absolute Stability. The most significant theoretical implication is that the class of neural circuits with a negative semidefinite T is the largest class of circuits that can be employed for embedding and solving optimization problems without the risk of spurious responses.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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