Radial basis function neural networks: a topical state-of-the-art survey

Radial basis function neural networks: a topical state-of-the-art survey

Radial basis function networks (RBFNs) have gained widespread appeal amongst researchers and have shown good performance in a variety of application domains. They have potential for hybridization and demonstrate some interesting emergent behaviors. This paper aims to offer a compendious and sensible...

Full description

Bibliographic Details
Main Authors: Dash Ch. Sanjeev Kumar, Behera Ajit Kumar, Dehuri Satchidananda, Cho Sung-Bae
Format: Article
Language:English
Published: De Gruyter 2016-05-01
Series:Open Computer Science
Subjects:
neural network
radial basis function networks
multi-criterions optimization
learning
classification
clustering
approximation
Online Access:https://doi.org/10.1515/comp-2016-0005

Internet

https://doi.org/10.1515/comp-2016-0005

Similar Items