Analyzing Stability of Equilibrium Points in Neural Networks: A General Approach

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dc.creatorTruccolo, Wilson A.
dc.creatorRangarajan, Govindan
dc.creatorChen, Yonghong
dc.creatorDing, Mingzhou
dc.date2004-05-21
dc.date.accessioned2026-07-25T23:11:33Z
dc.descriptionNetworks of coupled neural systems represent an important class of models in computational neuroscience. In some applications it is required that equilibrium points in these networks remain stable under parameter variations. Here we present a general methodology to yield explicit constraints on the coupling strengths to ensure the stability of the equilibrium point. Two models of coupled excitatory-inhibitory oscillators are used to illustrate the approach.
dc.description20 pages, 4 figures
dc.identifierhttps://arxiv.org/abs/cond-mat/0405505
dc.identifierhttp://arxiv.org/abs/cond-mat/0405505
dc.identifierNeural Networks, vol. 16, 1453-1460 (2003)
dc.identifier.urihttps://dspace.dare.co.zw/handle/123456789/96292
dc.subjectDisordered Systems and Neural Networks
dc.subjectNeurons and Cognition
dc.titleAnalyzing Stability of Equilibrium Points in Neural Networks: A General Approach
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