Performance analysis of LVQ algorithms: A statistical physics approach

Learning vector quantization (LVQ) constitutes a powerful and intuitive method for adaptive nearest prototype classification. However, original LVQ has been introduced based on heuristics and numerous modifications exist to achieve better convergence and stability. Recently, a mathematical foundation by means of a cost function has been proposed which, as a limiting case,

• Type: Journal
• Year: 2006
• Where: NN
• Authors: Anarta Ghosh, Michael Biehl, Barbara Hammer
• Keywords: Adaptive Nearest Prototype, Intuitive Method, Neural Networks, NN 2006, Vector Quantization