Adaptive dynamic neural network estimators
DEMETRIOS G. LAINIOTIS, Konstantinos N. Plataniotis · 2002
The problem of state estimation for linear or nonlinear models with unknown parameters is very important in many engineering problems. In this paper the solution to the problem of adaptive estimation for unknown state variable or chaotic models through the use of adaptive dynamic neural estimators is proposed. The proposed adaptive neural estimators are developed and their advantages are discussed. Extensive computer simulations of the application or the proposed adaptive neural estimator to state estimation as well as chaotic series prediction illustrate the effectiveness of the adaptive neural solution.>