Improving the generalization properties of radial basis function neural networks

Authors:
Chris Bishop
Affiliations:
Neural Networks Group, AEA Technology, Harwell Laboratory, Oxfordshire OX11 0RA, United Kingdom
Venue:
Neural Computation
Year:
1991

Citing 2
Cited 26

Self-organization and associative memory: 3rd edition

Self-organization and associative memory: 3rd edition
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations

Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations

Learning the Dynamic Neural Networks with the Improvement of Generalization Capabilities

ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Sensitivity analysis applied to the construction of radial basis function networks

Neural Networks
Significant vector learning to construct sparse kernel regression models

Neural Networks
Regularization in the selection of radial basis function centers

Neural Computation
Comparison of some neural network and scattered data approximations: The inverse manipulator kinematics example

Neural Computation
Multistage RBF neural network ensemble learning for exchange rates forecasting

Neurocomputing
Combined projection and kernel basis functions for classification in evolutionary neural networks

Neurocomputing
Improving the generalization performance of RBF neural networks using a linear regression technique

Expert Systems with Applications: An International Journal
Local regularization assisted orthogonal least squares regression

Neurocomputing
Classification by evolutionary generalised radial basis functions

International Journal of Hybrid Intelligent Systems - Advances in Intelligent Agent Systems
Probabilistic neural computing with advanced nanoscale MOSFETs

Neurocomputing
Generalized logistic regression models using neural network basis functions applied to the detection of banking crises

IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part III
Virtual sample generation using concurrent-self-organizing maps and its application for facial expression recognition

MMES'10 Proceedings of the 2010 international conference on Mathematical models for engineering science
A reliability-based RBF network ensemble model for foreign exchange rates predication

ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
Hybrid artificial neural networks: models, algorithms and data

IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
Parameter estimation of q-Gaussian Radial Basis Functions Neural Networks with a Hybrid Algorithm for binary classification

Neurocomputing
Improving radial basis function networks for human face recognition using a soft computing approach

SEAL'06 Proceedings of the 6th international conference on Simulated Evolution And Learning
Adaptive training of radial basis function networks using particle swarm optimization algorithm

ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
A new approach to sizing analog CMOS building blocks using pre-compiled neural network models

Analog Integrated Circuits and Signal Processing
Permanent disability classification by combining evolutionary Generalized Radial Basis Function and logistic regression methods

Expert Systems with Applications: An International Journal
Ordinal classification using hybrid artificial neural networks with projection and kernel basis functions

HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part II
Ensembles of evolutionary product unit or RBF neural networks for the identification of sound for pass-by noise test in vehicles

Neurocomputing
An improvement in RBF learning algorithm based on PSO for real time applications

Neurocomputing
Predicting patient survival after liver transplantation using evolutionary multi-objective artificial neural networks

Artificial Intelligence in Medicine
Improvement of RBF neural networks using Fuzzy-OSD algorithm in an online radar pulse classification system

Applied Soft Computing
On the construction of the relevance vector machine based on Bayesian Ying-Yang harmony learning

Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

An important feature of radial basis function neural networks is the existence of a fast, linear learning algorithm in a network capable of representing complex nonlinear mappings. Satisfactory generalization in these networks requires that the network mapping be sufficiently smooth. We show that a modification to the error functional allows smoothing to be introduced explicitly without significantly affecting the speed of training. A simple example is used to demonstrate the resulting improvement in the generalization properties of the network.