Regularization of Ill-Posed Point Neuron Models
نویسندگان
چکیده
منابع مشابه
Regularization of Ill-Posed Point Neuron Models
Point neuron models with a Heaviside firing rate function can be ill-posed. That is, the initial-condition-to-solution map might become discontinuous in finite time. If a Lipschitz continuous but steep firing rate function is employed, then standard ODE theory implies that such models are well-posed and can thus, approximately, be solved with finite precision arithmetic. We investigate whether ...
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We show that point-neuron models with a Heaviside firing rate function can be ill posed. More specifically, the initial-condition-to-solution map might become discontinuous in finite time. Consequently, if finite precision arithmetic is used, then it is virtually impossible to guarantee the accurate numerical solution of such models. If a smooth firing rate function is employed, then standard O...
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ژورنال
عنوان ژورنال: The Journal of Mathematical Neuroscience
سال: 2017
ISSN: 2190-8567
DOI: 10.1186/s13408-017-0049-1