ML Anthology

Identification Using Feedforward Networks

Asriel U. Levin, Kumpati S. Narendra
NeCo 1995 pp. 349-369
doi:10.1162/NECO.1995.7.2.349 /neco/1995/levin1995neco-identification/

Abstract

This paper is concerned with the identification of an unknown nonlinear dynamic system when only the inputs and outputs are accessible for measurement. Specifically we investigate the use of feedforward neural networks as models for the input-output behavior of such systems. Relying on the approximation capabilities of feedforward neural networks and under mild assumptions regarding the properties of the underlying nonlinear system, it is shown that there exists a feedforward network that for almost all inputs (an open and dense set) will display the input-output behavior of the system.

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Cite

Text

Levin and Narendra. "Identification Using Feedforward Networks." Neural Computation, 1995. doi:10.1162/NECO.1995.7.2.349

Markdown

[Levin and Narendra. "Identification Using Feedforward Networks." Neural Computation, 1995.](https://mlanthology.org/neco/1995/levin1995neco-identification/) doi:10.1162/NECO.1995.7.2.349

BibTeX

@article{levin1995neco-identification,
  title     = {{Identification Using Feedforward Networks}},
  author    = {Levin, Asriel U. and Narendra, Kumpati S.},
  journal   = {Neural Computation},
  year      = {1995},
  pages     = {349-369},
  doi       = {10.1162/NECO.1995.7.2.349},
  volume    = {7},
  url       = {https://mlanthology.org/neco/1995/levin1995neco-identification/}
}