Continuous time modeling of nonlinear systems: a neural network-based approach

A neural network-based approach for continuous-time modeling of nonlinear systems is presented. The approach is based on an implicit integrator and recurrent networks. The resulting continuous-time model (a set of ordinary differential equations) is capable of correctly capturing the long term attractors of the system.<>