


default search action
Neurocomputing, Volume 29
Volume 29, Number 1-3, November 1999
- André Elisseeff, Hélène Paugam-Moisy:

JNN, a randomized algorithm for training multilayer networks in polynomial time. 3-24 - Max H. Garzon, Fernanda Botelho:

Dynamical approximation by recurrent neural networks. 25-46 - Paul C. Kainen, Vera Kurková

, Andrew Vogt:
Approximation by neural networks is not continuous. 47-56 - Aleksander Kolcz, Nigel M. Allinson

:
The general memory neural network and its relationship with basis function architectures. 57-84 - Sethu Vijayakumar, Hidemitsu Ogawa:

RKHS-based functional analysis for exact incremental learning. 85-113 - Nageswara S. V. Rao

:
Simple sample bound for feedforward sigmoid networks with bounded weights. 115-122

manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.


Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCID














