Multilayer feedforward networks are universal approximators
Neural Networks
Inductively inferring valid logical models of continuous-state dynamical systems
Theoretical Computer Science - Special issue on hybrid systems
Adaptive behavior form fixed weight networks
Information Sciences: an International Journal
Neural Computation
Complete memory structures for approximating nonlinear discrete-time mappings
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Hi-index | 0.00 |
Recently, there has been interest in the observed capabilities of some classes of neural networks with fixed weights to model multiple nonlinear dynamical systems. While this property has been observed in simulations, open questions exist as to how this property can arise. In this article, we propose a theory that provides a possible mechanism by which this multiple modeling phenomenon can occur.