ML Anthology

Gram - Schmidt Neural Nets

Sophocles J. Orfanidis
NeCo 1990 pp. 116-126
doi:10.1162/NECO.1990.2.1.116 /neco/1990/orfanidis1990neco-gram/

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.

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Cite

Text

Orfanidis. "Gram - Schmidt Neural Nets." Neural Computation, 1990. doi:10.1162/NECO.1990.2.1.116

Markdown

[Orfanidis. "Gram - Schmidt Neural Nets." Neural Computation, 1990.](https://mlanthology.org/neco/1990/orfanidis1990neco-gram/) doi:10.1162/NECO.1990.2.1.116

BibTeX

@article{orfanidis1990neco-gram,
  title     = {{Gram - Schmidt Neural Nets}},
  author    = {Orfanidis, Sophocles J.},
  journal   = {Neural Computation},
  year      = {1990},
  pages     = {116-126},
  doi       = {10.1162/NECO.1990.2.1.116},
  volume    = {2},
  url       = {https://mlanthology.org/neco/1990/orfanidis1990neco-gram/}
}