T. Kohonen, Self-Organizing MapsNew, extended edition in 2001!
Springer Series in Information Sciences, Vol. 30, Springer, Berlin,
Heidelberg, New York, 1995, 1997, 2001. Third Extended Edition, 501 pages.
Self-Organizing Map (SOM), with its variants, is the most popular artificial neural network algorithm in the unsupervised learning category. About 4000 research articles on it have appeared in the open literature, and many industrial projects use the SOM as a tool for solving hard real-world problems. Many fields of science have adopted the SOM as a standard analytical tool: statistics, signal processing, control theory, financial analysis, experimental physics, chemistry and medicine. The SOM solves difficult high-dimensional and nonlinear problems such as feature extraction and classification of images and acoustic patterns, adaptive control of robots, and equalization, demodulation, and error-tolerant transmission of signals in telecommunications. A new area is the organization of very large document collections. Last but not least, it should be mentioned that the SOM is one of the most realistic models of the biological brain function.
Note: The third edition contains 501 pages. Changes with respect to the second edition include about 20 deleted pages and 100 completely new pages.
Tuesday, 30-Jan-2001 11:21:55 EET