Title :
Regressor selection and wavelet network construction
Author_Institution :
IRISA, Rennes, France
Abstract :
The wavelet network has been introduced as a special feedforward neural network supported by the wavelet theory. In this paper the construction of feedforward neural networks is discussed from the regressor selection point of view. This reveals that the wavelet network structure is well suited for developing constructive methods of feedforward networks. An efficient construction procedure of the wavelet network based on the orthogonal least squares method is then proposed
Keywords :
feedforward neural nets; least squares approximations; statistical analysis; wavelet transforms; feedforward neural network; orthogonal least squares method; regressor selection; wavelet network; wavelet theory; Automatic control; Feedforward neural networks; Least squares approximation; Least squares methods; Multi-layer neural network; Neural networks; Neurons; Nonlinear systems; Pattern recognition; Signal processing;
Conference_Titel :
Decision and Control, 1993., Proceedings of the 32nd IEEE Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
0-7803-1298-8
DOI :
10.1109/CDC.1993.325905
