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000000233 245__ $$aKohonen Self-Organizing Map with quantized weights
000000233 260__ $$bElsevier$$c1999
000000233 269__ $$a1999
000000233 336__ $$aBook Chapters
000000233 520__ $$aPreface
 Analyzing and representing multidimensional quantitative and qualitative data: Demographic study of the Rhône valley. The domestic consumption of the Canadian families
 Value Maps: Finding Value in Markets that are Expensive
 Data Mining and Knowledge Discovery with Emergent Self-Organizing Feature Maps for Multivariate Time Series
 From Aggregation Operators to Soft Learning Vector Quantization and Clustering Algorithms
 Active Learning in Self-Organizing Maps
 Point Prototype Generation and Classifier Design
 Self-Organizing Maps on non-euclidean Spaces
 Self-Organising Maps for Pattern Recognition
 Tree Structured Self-Organizing Maps
 Growing self-organizing networks—history, status quo, and perspectives
 Kohonen Self-Organizing Map with quantized weights
 On the Optimization of Self-Organizing Maps by Genetic Algorithms
 Self organization of a massive text document collection
 Document Classification with Self-Organizing Maps
 Navigation in Databases Using Self-Organising Maps
 A SOM-based sensing approach to robotic manipulation tasks
 SOM-TSP: An approach to optimize surface component mounting on a printed circuit board
 Self-Organising Maps in Computer Aided Design of electronic circuits
 Modeling Self-Organization in the Visual Cortex
 A Spatio-Temporal Memory Based on SOMs with Activity Diffusion
 Advances in modeling cortical maps
 Topology Preservation in Self-Organizing Maps
 Second-Order Learning in Self-Organizing Maps
 Energy functions for self-organizing maps
 LVQ and single trial EEG classification
 Self-organizing map in categorization of voice qualities
 Chemometric analyses with self organising feature maps: A worked example of the analysis of cosmetics using Raman spectroscopy
 Self-Organizing Maps for Content-Based Image Database Retrieval
 Indexing Audio Documents by using Latent Semantic Analysis and SOM
 Self-Organizing map in analysis of large-scale industrial systems
 Keyword index
 
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 Kohonen Maps
 
 1999, Pages 145–156
 
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 Kohonen Self-Organizing Map with quantized weights
 
 P. Thirana, 
 
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 doi:10.1016/B978-044450270-4/50011-5
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 Publisher Summary
 
 The purpose of this chapter is to review the convergence properties of the Kohonen self-organizing map (SOM) when the inputs and the weights are quantized. The motivation behind this work and the impact of the results are both of theoretical and practical nature, and it will not be possible to implement it on a digital very-large-scale integration (VLSI) chip. Most of the chapter is focused on the rigorous analysis in the 1-dim setting, where both the weights and the inputs are scalar. Necessary and sufficient conditions for the ordering of scalar quantized weights are established. These results are compared with the ones obtained when the weights are continuous-valued. Finally, it confirms qualitatively this analysis for the 2-dim case.
000000233 700__ $$0240373$$aThiran, Patrick$$g103925
000000233 720_1 $$aOja, Erkki$$eed.
000000233 720_1 $$aKaski, Samuel$$eed.
000000233 773__ $$q145-156$$tKohonen Maps
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