Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Neural computers. --- Neural networks (Computer science). --- Self-organizing maps.

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

The self-organizing map, first described by the Finnish scientist Teuvo Kohonen, can by applied to a wide range of fields. This book is about such applications, i.e. how the original self-organizing map as well as variants and extensions of it can be applied in different fields. In fourteen chapters, a wide range of such applications is discussed. To name a few, these applications include the analysis of financial stability, the fault diagnosis of plants, the creation of well-composed heterogeneous teams and the application of the self-organizing map to the atmospheric sciences.

Self-organizing maps. --- Algorithms, Kohonen --- Kohonen algorithms --- Kohonen maps --- Kohonen's maps --- Maps, Kohonen --- Maps, Self-organizing --- SOMs (Self-organizing maps) --- Neural networks (Computer science) --- Self-organizing systems --- Human-computer interaction

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This book focuses on the research topics investigated during the three-year research project funded by the Italian Ministero dell'Istruzione, dell'Università e della Ricerca (MIUR: Ministry of Education, University and Research) under the FIRB project RBNE01CW3M. With the aim of introducing newer perspectives of the research on complexity, the final results of the project are presented after a general introduction to the subject. The book is intended to provide researchers, PhD students, and people involved in research projects in companies with the basic fundamentals of complex systems and th

Computational complexity. --- Nonlinear systems --- Self-organizing maps. --- System theory --- Systems, Theory of --- Systems science --- Science --- Algorithms, Kohonen --- Kohonen algorithms --- Kohonen maps --- Kohonen's maps --- Maps, Kohonen --- Maps, Self-organizing --- SOMs (Self-organizing maps) --- Neural networks (Computer science) --- Self-organizing systems --- Systems, Nonlinear --- Complexity, Computational --- Electronic data processing --- Machine theory --- Mathematical models. --- Philosophy --- Computational Complexity --- Self-organizing maps --- Mathematical models --- Nonlinear systems - Mathematical models --- System theory - Mathematical models

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Artificial intelligence. Robotics. Simulation. Graphics --- Neural networks (Computer science) --- Self-organizing systems --- Réseaux neuronaux (Informatique) --- Systèmes auto-organisés --- Self-organizing maps. --- Self-organizing maps --- 681.3*I51 --- Algorithms, Kohonen --- Kohonen algorithms --- Kohonen maps --- Kohonen's maps --- Maps, Kohonen --- Maps, Self-organizing --- SOMs (Self-organizing maps) --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Artificial intelligence --- Natural computation --- Soft computing --- Models: deterministic; fuzzy set; geometric; statistical; structural (Patternrecognition) --- Neural networks (Computer science). --- 681.3*I51 Models: deterministic; fuzzy set; geometric; statistical; structural (Patternrecognition) --- Réseaux neuronaux (Informatique) --- Systèmes auto-organisés

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

The 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: in statistics, signal processing, control theory, financial analyses, 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 organization of very large document collections. Last but not least, it may be mentioned that the SOM is one of the most realistic models of the biological brain function. This new edition includes a survey of over 2000 contemporary studies to cover the newest results; case examples were provided with detailed formulae, illustrations, and tables; a new chapter on Software Tools for SOM was written, other chapters were extended or reorganized.

Neural networks (Computer science). --- Self-organizing maps. --- Neural networks (Computer science) --- Self-organizing maps --- Telecommunication. --- Statistical physics. --- Complex Systems. --- Biological and Medical Physics, Biophysics. --- Communications Engineering, Networks. --- Statistical Physics and Dynamical Systems. --- Physics --- Mathematical statistics --- Electric communication --- Mass communication --- Telecom --- Telecommunication industry --- Telecommunications --- Communication --- Information theory --- Telecommuting --- Statistical methods --- Dynamical systems. --- Biophysics. --- Biological physics. --- Electrical engineering. --- Electric engineering --- Engineering --- Biological physics --- Biology --- Medical sciences --- Dynamical systems --- Kinetics --- Mathematics --- Mechanics, Analytic --- Force and energy --- Mechanics --- Statics