Gopalakrishnan, M and Sridhar, V and Krishnamurthy, H (1995) Some applications of clustering in the design of neural networks. In: Pattern Recognition Letters, 16 (1). pp. 59-65.
Restricted to Registered users only
Download (465Kb) | Request a copy
In this paper, we discuss the role of clustering techniques in the design of neural networks. Specifically, we address the issue in relation to two network paradigms: one based on back-propagation and the other based on radial basis functions. In the former case, we demonstrate, emprically, that by employing clustering techniques, the training effort may be drastically brought down. In the latter case, we demonstrate that clustering techniques can be employed to build more robust classifiers. We also discuss the role of clustering in the design of hierarchical systems. Specifically, we discuss a hierarchical system based on radial basis functions.
|Item Type:||Journal Article|
|Additional Information:||The copyright belongs to Elsevier.|
|Keywords:||Back propagation;Clustering;Neural networks;Radial basis functions;Training algorithms|
|Department/Centre:||Division of Information Sciences > Supercomputer Education & Research Centre|
|Date Deposited:||14 Jun 2006|
|Last Modified:||19 Sep 2010 04:29|
Actions (login required)