Gram—Schmidt Neural Nets
- 1 March 1990
- journal article
- Published by MIT Press in Neural Computation
- Vol. 2 (1) , 116-126
- https://doi.org/10.1162/neco.1990.2.1.116
Abstract
A new type of feedforward multilayer neural net is proposed that exhibits fast convergence properties. It is defined by inserting a fast adaptive Gram-Schmidt preprocessor at each layer, followed by a conventional linear combiner-sigmoid part which is adapted by a fast version of the backpropagation rule. The resulting network structure is the multilayer generalization of the gradient adaptive lattice filter and the Gram-Schmidt adaptive array.Keywords
This publication has 1 reference indexed in Scilit:
- Increased rates of convergence through learning rate adaptationNeural Networks, 1988