On Stability and Model Order Reduction of Perturbed Nonlinear Neural Networks
نویسندگان
چکیده
In this paper, the qualitative theory of large-scale dynamical systems is surveyed. In particular, the focus is the Hopfield Neural networks both with and without perturbations. Properties relating to asymptotic and exponential stability and instability are detailed. A model reduction technique based on balanced truncation is applied to the neural networks. Its effect on the stability properties of the networks is then examined. A numerical test illustrates some important points.
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