Kalman filtering and neural networks serves as an expert resource for researchers in neural networks and nonlinear dynamical systems reviews although the traditional approach to the subject is usually linear this book recognizes and deals with the fact that real problems are most often nonlinear. The kalman filter rooted in the state space formulation of linear dynamical systems provides a recursive solution to the linear optimal filtering problem it applies to stationary as well as nonstationary environments the solution is recursive in that each updated estimate of the state is computed from the previous estimate and the new input data so only the previous estimate requires storage in this chapter an introductory treatment of kalman filters is presented. Kalman filtering and neural networks edited by simon haykin copyright 2001 john wiley sons inc isbns 0 471 36998 5 hardback 0 471 22154 6 electronic. The kalman filter rooted in the state space formulation of linear dynamical systems provides a recursive solution to the linear optimal filtering problem it applies to stationary as well as nonstationary environments the solution is recursive in that each updated estimate of the state is computed from the previous estimate and the new input data so only the previous estimate requires