Kohonen Maps
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Kohonen Maps
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Author : E. Oja
language : en
Publisher: Elsevier
Release Date : 1999-07-02
Kohonen Maps written by E. Oja and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-07-02 with Computers categories.
The Self-Organizing Map, or Kohonen Map, is one of the most widely used neural network algorithms, with thousands of applications covered in the literature. It was one of the strong underlying factors in the popularity of neural networks starting in the early 80's. Currently this method has been included in a large number of commercial and public domain software packages. In this book, top experts on the SOM method take a look at the state of the art and the future of this computing paradigm. The 30 chapters of this book cover the current status of SOM theory, such as connections of SOM to clustering, classification, probabilistic models, and energy functions. Many applications of the SOM are given, with data mining and exploratory data analysis the central topic, applied to large databases of financial data, medical data, free-form text documents, digital images, speech, and process measurements. Biological models related to the SOM are also discussed.
Self Organizing Maps
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Author : Teuvo Kohonen
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Self Organizing Maps written by Teuvo Kohonen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Science categories.
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: statistics, signal processing, control theory, financial analyses, experimental physics, chemistry and medicine. This new edition includes a survey of over 2000 contemporary studies to cover the newest results. Case examples are provided with detailed formulae, illustrations, and tables. Further, a new chapter on software tools for SOM has been included whilst other chapters have been extended and reorganised.
Self Organizing Maps
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Author : Josphat Igadwa Mwasiagi
language : en
Publisher: BoD – Books on Demand
Release Date : 2011-01-21
Self Organizing Maps written by Josphat Igadwa Mwasiagi and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-21 with Computers categories.
Kohonen Self Organizing Maps (SOM) has found application in practical all fields, especially those which tend to handle high dimensional data. SOM can be used for the clustering of genes in the medical field, the study of multi-media and web based contents and in the transportation industry, just to name a few. Apart from the aforementioned areas this book also covers the study of complex data found in meteorological and remotely sensed images acquired using satellite sensing. Data management and envelopment analysis has also been covered. The application of SOM in mechanical and manufacturing engineering forms another important area of this book. The final section of this book, addresses the design and application of novel variants of SOM algorithms.
Applications Of Self Organizing Maps
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Author : Magnus Johnsson
language : en
Publisher: BoD – Books on Demand
Release Date : 2012-11-21
Applications Of Self Organizing Maps written by Magnus Johnsson and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-21 with Computers categories.
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.
Advances In Self Organizing Maps
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Author : Pablo A. Estévez
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-14
Advances In Self Organizing Maps written by Pablo A. Estévez and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-14 with Technology & Engineering categories.
Self-organizing maps (SOMs) were developed by Teuvo Kohonen in the early eighties. Since then more than 10,000 works have been based on SOMs. SOMs are unsupervised neural networks useful for clustering and visualization purposes. Many SOM applications have been developed in engineering and science, and other fields. This book contains refereed papers presented at the 9th Workshop on Self-Organizing Maps (WSOM 2012) held at the Universidad de Chile, Santiago, Chile, on December 12-14, 2012. The workshop brought together researchers and practitioners in the field of self-organizing systems. Among the book chapters there are excellent examples of the use of SOMs in agriculture, computer science, data visualization, health systems, economics, engineering, social sciences, text and image analysis, and time series analysis. Other chapters present the latest theoretical work on SOMs as well as Learning Vector Quantization (LVQ) methods.
Advances In Self Organizing Maps Learning Vector Quantization Clustering And Data Visualization
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Author : Jan Faigl
language : en
Publisher: Springer Nature
Release Date : 2022-08-26
Advances In Self Organizing Maps Learning Vector Quantization Clustering And Data Visualization written by Jan Faigl and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-26 with Technology & Engineering categories.
In this collection, the reader can find recent advancements in self-organizing maps (SOMs) and learning vector quantization (LVQ), including progressive ideas on exploiting features of parallel computing. The collection is balanced in presenting novel theoretical contributions with applied results in traditional fields of SOMs, such as visualization problems and data analysis. Besides, the collection further includes less traditional deployments in trajectory clustering and recent results on exploiting quantum computation. The presented book is worth interest to data analysis and machine learning researchers and practitioners, specifically those interested in being updated with current developments in unsupervised learning, data visualization, and self-organization.
On The Biological Implementation Of Kohonen Maps
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Author : Alexander S. Tepper
language : en
Publisher:
Release Date : 2001
On The Biological Implementation Of Kohonen Maps written by Alexander S. Tepper and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with categories.
Self Organizing Map Formation
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Author : Klaus Obermayer
language : en
Publisher: MIT Press
Release Date : 2001
Self Organizing Map Formation written by Klaus Obermayer and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Neural computers categories.
This book provides an overview of self-organizing map formation, including recent developments. Self-organizing maps form a branch of unsupervised learning, which is the study of what can be determined about the statistical properties of input data without explicit feedback from a teacher. The articles are drawn from the journal Neural Computation.The book consists of five sections. The first section looks at attempts to model the organization of cortical maps and at the theory and applications of the related artificial neural network algorithms. The second section analyzes topographic maps and their formation via objective functions. The third section discusses cortical maps of stimulus features. The fourth section discusses self-organizing maps for unsupervised data analysis. The fifth section discusses extensions of self-organizing maps, including two surprising applications of mapping algorithms to standard computer science problems: combinatorial optimization and sorting. Contributors J. J. Atick, H. G. Barrow, H. U. Bauer, C. M. Bishop, H. J. Bray, J. Bruske, J. M. L. Budd, M. Budinich, V. Cherkassky, J. Cowan, R. Durbin, E. Erwin, G. J. Goodhill, T. Graepel, D. Grier, S. Kaski, T. Kohonen, H. Lappalainen, Z. Li, J. Lin, R. Linsker, S. P. Luttrell, D. J. C. MacKay, K. D. Miller, G. Mitchison, F. Mulier, K. Obermayer, C. Piepenbrock, H. Ritter, K. Schulten, T. J. Sejnowski, S. Smirnakis, G. Sommer, M. Svensen, R. Szeliski, A. Utsugi, C. K. I. Williams, L. Wiskott, L. Xu, A. Yuille, J. Zhang
Self Organising Maps
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Author : Pragya Agarwal
language : en
Publisher: John Wiley & Sons
Release Date : 2008-04-15
Self Organising Maps written by Pragya Agarwal and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-04-15 with Science categories.
Self-Organising Maps: Applications in GI Science brings together the latest geographical research where extensive use has been made of the SOM algorithm, and provides readers with a snapshot of these tools that can then be adapted and used in new research projects. The book begins with an overview of the SOM technique and the most commonly used (and freely available) software; it is then sectioned to look at the different uses of the technique, namely clustering, data mining and cartography, from a range of application-areas in the biophysical and socio-economic environments. Only book that takes SOM algorithm to the GIS and Geography research communities The Editors draw together expert contributors from the UK, Europe, USA, New Zealand, and South Africa Covers a range of techniques in clustering, data mining cartography, all featuring an appropriate case study
Improvements Quality Of Kohonen Maps Using Dimension Reduction Methods
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Author : Jiri Dvorsky
language : en
Publisher:
Release Date : 2010
Improvements Quality Of Kohonen Maps Using Dimension Reduction Methods written by Jiri Dvorsky and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.
Alternative approach of quality measurement of the SOM learning process was presented. This approach uses SVD decomposition of the SOM, and number of moved BMUs are counted among each consecutive rank-k approximations of original SOM. Our experiments show some properties of SVD decomposition of SOM. That is new and good. On the other hand HOSVD cause some problems, because number of moved BMUs is very high. It seems that SOM is not true three dimensional object the third dimension consisting of neurons is not relevant. We should check if this behavior is feature or bug of this method or if it is a matter of coincidence. This is new and quite disappointing. Usage of Non-negative Matrix Factorization (Golub & Loan, 1996) is our goal in future research. The second goal is application of presented method on the other type of neural network, such as Growing Neural Gas (Fritzke, 1994).