Application of neural networks to nonlinear filtering
William R. Michalson · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1992
The application of neural networks to learning nonlinear functions for use in filters and control systems is discussed. Several examples characterize the quality of learning that takes place and the performance of the neural network in the presence of noisy inputs. A final example compares a neural network-based filter to an optimal Kalman filter for a simple quadratic system.