Neural Networks 14(10)

[Cynthia Bradford]

NEURAL NETWORKS 14(10)
Contents - Volume 14, Number 10 - 2001

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CONTRIBUTED ARTICLES:

***** Psychology and Cognitive Science ***** 

Connectionist inference models
Antony Browne and Ron Sun 


***** Neuroscience and Neuropsychology ***** 

Analysis of the frequency response of the saccadic circuit: 
Numerical simulations 
Mark E. Jackson, Oleg Litvak, and James W. Gnadt 


***** Mathematical and Computational Analysis *****

Unified stabilization approach to principal and minor components
extraction algorithms 
Tianping Chen and Shun-ichi Amari 

Improvement of generalization ability for identifying dynamic 
systems by using universal learning networks
Kotaro Hirasawa, Sung-ho Kim, Jinglu Hu, Junichi Murata, 
Min Han, and Chunzhi Jin 

Self-organization in the one-dimensional SOM with a decreasing 
neighborhood
John A. Flanagan 

Upper bound of the expected training error of neural network 
regression for a Gaussian noise sequence
Katsuyuki Hagiwara, Taichi Hayasaka, Naohiro Toda, Shiro Usui, 
and Kazuhiro Kuno 

The POP learning algorithms: Reducing work in identifying fuzzy rules
C. Quek and R.W. Zhou 


***** Engineering & Design *****

Oriented principal component analysis for large margin classifiers
Sergio Bermejo and Joan Cabestany 


***** Letters to the Editor ***** 

A remark on "On stability of nonlinear continuous-time neural 
networks with delays"
Yuming Chen 

On using the Poincare polynomial for calculating the V-C dimension 
of neural networks
Michael Schmitt

Response: On using the Poincare polynomial for calculating the 
V-C dimension of neural networks
Martha A. Carter and Mark E. Oxley


***** Erratum ***** 

Evaluating the Vapnik-Chervonenkis dimension of artificial neural 
networks using the Poincare polynomial 
(Neural Networks, 1999, 12, 403-408)
Martha A. Carter and Mark E. Oxley 


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