Title :
Time series prediction with linear and nonlinear adaptive networks
Author :
Coughlin, James P. ; Baran, Robert
Author_Institution :
Dept. of Math., Towson State Univ., MD, USA
Abstract :
Backpropagation networks with a single hidden layer were trained to perform one-step prediction on a variety of scalar time series. The performance of such nets typically equals or exceeds that of the linear adaptive predictor of the same order. Comparisons of the linear and nonlinear predictors were made with periodic, chaotic, and random time series, including broadband ocean acoustic ambient noise
Keywords :
adaptive systems; filtering and prediction theory; learning systems; neural nets; time series; backpropagation networks; broadband ocean acoustic ambient noise; linear adaptive networks; neural nets; nonlinear adaptive networks; random time series; scalar time series; time series prediction; Adaptive filters; Adaptive systems; Backpropagation; Chaos; Mathematics; Neural networks; Nonlinear equations; Sea surface; Silver; Springs;
Conference_Titel :
Neural Networks, 1991. 1991 IEEE International Joint Conference on
Print_ISBN :
0-7803-0227-3
DOI :
10.1109/IJCNN.1991.170431
