๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

A filter based neuron model for adaptive incremental learning of self-organizing maps

โœ Scribed by Mauro Tucci; Marco Raugi


Publisher
Elsevier Science
Year
2011
Tongue
English
Weight
471 KB
Volume
74
Category
Article
ISSN
0925-2312

No coin nor oath required. For personal study only.


๐Ÿ“œ SIMILAR VOLUMES


Self-organization of orientation maps in
โœ J. Kuroiwa; S. Inawashiro; S. Miyake; H. Aso ๐Ÿ“‚ Article ๐Ÿ“… 2000 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 496 KB

Self-organization of orientation maps due to external stimuli in the primary visual area of the cerebral cortex is studied in a two-layered neural network which consists of formal neuron models with a sigmoidal output function. A cluster learning rule is proposed as an extended Hebbian learning rule

Hypercolumn model: A combination model o
โœ Naoyuki Tsuruta; Rin-ichiro Taniguchi; Makoto Amamiya ๐Ÿ“‚ Article ๐Ÿ“… 2000 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 702 KB

In this paper, a neural network model, the hypercolumn model (HCM), which is applicable to general image recognition, is proposed. The HCM is a combination model of hierarchical self-organizing maps (HSOM) and neocognitron (NC); it resolves the disadvantages of both the HSOM and the NC, and inherits