๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Generating fuzzy membership function with self-organizing feature map

โœ Scribed by Chih-Chung Yang; N.K. Bose

Publisher
Elsevier Science
Year
2006
Tongue
English
Weight
310 KB
Volume
27
Category
Article
ISSN
0167-8655

No coin nor oath required. For personal study only.

๐Ÿ“œ SIMILAR VOLUMES

Generalized fuzzy inference neural netwo
Generalized fuzzy inference neural network using a self-organizing feature map
โœ Hiroshi Kitajima; Masafumi Hagiwara ๐Ÿ“‚ Article ๐Ÿ“… 1999 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 194 KB ๐Ÿ‘ 2 views

A new model for generalized fuzzy inference neural networks (GFINN) is proposed in this paper. The networks consist of three layers: an input-output layer, an if layer, and a then layer. In each layer, there are the operational nodes. A GFINN can perform three representative fuzzy inference methods

Dynamic generation of prototypes with se
Dynamic generation of prototypes with self-organizing feature maps for classifier design
โœ Arijit Laha; Nikhil R. Pal ๐Ÿ“‚ Article ๐Ÿ“… 2001 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 161 KB

We propose a new scheme for designing a nearest-prototype classi"er using Kohonen's self-organizing feature map (SOFM). The net starts with the minimum number of prototypes which is equal to the number of classes. Then on the basis of the classi"cation performance, new prototypes are generated dynam

Self-organization property of Kohonen's
Self-organization property of Kohonen's map with general type of stimuli distribution
โœ Ali A. Sadeghi ๐Ÿ“‚ Article ๐Ÿ“… 1998 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 124 KB

Here the self-organization property of one-dimensional Kohonen's algorithm in its 2k ยน neighbor setting with a general type of stimuli distribution and non-increasing learning rate is considered. A new definition of the winner is given, which coincides with the usual definition in implementations of