Modeling Time Varying Systems Using a Hidden Control Neural Network Architecture

Modeling time varying systems is important for many applications, such as speech and image processing. In this paper we propose a novel method for modeling signals generated by nonlinear dynamical systems with restricted time variability. We present a network architecture, the 'Hidden Control Neural Network' which is capable of dealing with the time varying parameters by adding an undetermined control signal to the network.