The Self-Organizing Map (SOM) algorithm has attracted a great deal of interest among researches and practitioners in a wide variety of fields. The SOM has been analyzed extensively, a number of variants have been developed and, perhaps most notably, it has been applied extensively within fields ranging from engineering sciences to medicine, biology, and economics. We have collected a comprehensive list of 5384 scientific papers that use the algorithms, have benefited from them, or contain analyses of them. The list is intended to serve as a source for literature surveys. The present addendum contains 2092 new articles, mainly from the years 1998-2002. We have provided a keyword index to help finding articles of interest, and additionally a modern automatically constructed variant of a thematic index: a WEBSOM interface to the whole article collection of years 1981-2000. The SOM of SOMs is available at http://websom.hut.fi/websom/somref/search.cgi for browsing and searching the collection.

Bibliography of Self-Organizing Map SOM) Papers: 1998-2001 Addendum

A VLSI architecture for 3-D self-organizing map based color quantization and its FPGA implementation

This paper proposes a system for the automatic hardware design of neural networks based on cooperative coevolutionary paradigms and multiple reconfigurable devices. The authors' system is composed of a logic synthesis tool, multiple reconfigurable devices and an embedded processor executing the coevolutionary algorithm. The partitioning of the engineering design process follows current practices in hardware/software codesign based on both information on arrival rate /spl lambda/ of requests and the service time /spl mu/ of the reconfigurable devices. The system is suitable under some conditions for industrial applications such as a reactive system but also because it can be connected to multiple systems in a totally networked industrial environment which allows download of the same hardware configuration on multiple on ine devices.

Coevolvable hardware platform for automatic hardware design of neural networks

The damage of the Previous Crossed Ligament (LCA) has been one of the most widely and varied studied pathologies. We have experimented with both direct and i...

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Sistema de análisis de patrones implementado en FPGAs para el estudio experimental de los ligamentos en la articulación

This paper describes the hardware design of a multi-FPGA hardware implementation of a 16 neurons Self-Organizing Map (SOM) artificial neural network. The SOM designed includes 16 neurons controlled in a SIMD execution mode. The application targeted is 3D to 2D projection. The clock frequency of the hardware design is 11.386 MHz and it has been implemented on 5 Xilinx FPGA chips mounted on a plug-an-play PC ISA board. The resulting hardware outperforms under some conditions several software simulations implementations running on various PC hardware.

D. Suzuki

Papers

SOM on multi-FPGA ISA board-hardware aspects