Neural Computation And Self Organizing Maps

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Self-organizing Map Formation

Author : Klaus Obermayer
Publisher : MIT Press
ISBN 13 : 9780262650601
Total Pages : 472 pages
Book Rating : 4.6/5 (56 download)

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Book Synopsis Self-organizing Map Formation by : Klaus Obermayer

Download or read book Self-organizing Map Formation written by Klaus Obermayer and published by MIT Press. This book was released on 2001 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Neural Computation and Self-organizing Maps

Author : Helge Ritter
Publisher : Addison Wesley Publishing Company
ISBN 13 :
Total Pages : 328 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Neural Computation and Self-organizing Maps by : Helge Ritter

Download or read book Neural Computation and Self-organizing Maps written by Helge Ritter and published by Addison Wesley Publishing Company. This book was released on 1992 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Neural Computation and Self-organizing Maps

Author : Helge Ritter
Publisher : Addison Wesley Publishing Company
ISBN 13 : 9780201554434
Total Pages : 0 pages
Book Rating : 4.5/5 (544 download)

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Book Synopsis Neural Computation and Self-organizing Maps by : Helge Ritter

Download or read book Neural Computation and Self-organizing Maps written by Helge Ritter and published by Addison Wesley Publishing Company. This book was released on 1992 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Self-Organizing Maps

Author : Teuvo Kohonen
Publisher : Springer Science & Business Media
ISBN 13 : 3642976107
Total Pages : 372 pages
Book Rating : 4.6/5 (429 download)

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Book Synopsis Self-Organizing Maps by : Teuvo Kohonen

Download or read book Self-Organizing Maps written by Teuvo Kohonen and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book we have at hand is the fourth monograph I wrote for Springer Verlag. The previous one named "Self-Organization and Associative Mem ory" (Springer Series in Information Sciences, Volume 8) came out in 1984. Since then the self-organizing neural-network algorithms called SOM and LVQ have become very popular, as can be seen from the many works re viewed in Chap. 9. The new results obtained in the past ten years or so have warranted a new monograph. Over these years I have also answered lots of questions; they have influenced the contents of the present book. I hope it would be of some interest and help to the readers if I now first very briefly describe the various phases that led to my present SOM research, and the reasons underlying each new step. I became interested in neural networks around 1960, but could not in terrupt my graduate studies in physics. After I was appointed Professor of Electronics in 1965, it still took some years to organize teaching at the uni versity. In 1968 - 69 I was on leave at the University of Washington, and D. Gabor had just published his convolution-correlation model of autoasso ciative memory. I noticed immediately that there was something not quite right about it: the capacity was very poor and the inherent noise and crosstalk were intolerable. In 1970 I therefore sugge~ted the auto associative correlation matrix memory model, at the same time as J.A. Anderson and K. Nakano.

Self-Organizing Maps

Author : Teuvo Kohonen
Publisher : Springer Science & Business Media
ISBN 13 : 3642569277
Total Pages : 514 pages
Book Rating : 4.6/5 (425 download)

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Book Synopsis Self-Organizing Maps by : Teuvo Kohonen

Download or read book Self-Organizing Maps written by Teuvo Kohonen and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Neural Networks

Author : Udo Seiffert
Publisher : Physica
ISBN 13 : 3790818100
Total Pages : 289 pages
Book Rating : 4.7/5 (98 download)

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Book Synopsis Self-Organizing Neural Networks by : Udo Seiffert

Download or read book Self-Organizing Neural Networks written by Udo Seiffert and published by Physica. This book was released on 2013-11-11 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Self-Organizing Map (SOM) is one of the most frequently used architectures for unsupervised artificial neural networks. Introduced by Teuvo Kohonen in the 1980s, SOMs have been developed as a very powerful method for visualization and unsupervised classification tasks by an active and innovative community of interna tional researchers. A number of extensions and modifications have been developed during the last two decades. The reason is surely not that the original algorithm was imperfect or inad equate. It is rather the universal applicability and easy handling of the SOM. Com pared to many other network paradigms, only a few parameters need to be arranged and thus also for a beginner the network leads to useful and reliable results. Never theless there is scope for improvements and sophisticated new developments as this book impressively demonstrates. The number of published applications utilizing the SOM appears to be unending. As the title of this book indicates, the reader will benefit from some of the latest the oretical developments and will become acquainted with a number of challenging real-world applications. Our aim in producing this book has been to provide an up to-date treatment of the field of self-organizing neural networks, which will be ac cessible to researchers, practitioners and graduated students from diverse disciplines in academics and industry. We are very grateful to the father of the SOMs, Professor Teuvo Kohonen for sup porting this book and contributing the first chapter.

Self Organizing Maps

Author : Josphat Igadwa Mwasiagi
Publisher : BoD – Books on Demand
ISBN 13 : 9533075465
Total Pages : 717 pages
Book Rating : 4.5/5 (33 download)

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Book Synopsis Self Organizing Maps by : Josphat Igadwa Mwasiagi

Download or read book Self Organizing Maps written by Josphat Igadwa Mwasiagi and published by BoD – Books on Demand. This book was released on 2011-01-21 with total page 717 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Computational Intelligence Systems in Industrial Engineering

Author : Cengiz Kahraman
Publisher : Springer Science & Business Media
ISBN 13 : 9491216775
Total Pages : 683 pages
Book Rating : 4.4/5 (912 download)

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Book Synopsis Computational Intelligence Systems in Industrial Engineering by : Cengiz Kahraman

Download or read book Computational Intelligence Systems in Industrial Engineering written by Cengiz Kahraman and published by Springer Science & Business Media. This book was released on 2012-11-05 with total page 683 pages. Available in PDF, EPUB and Kindle. Book excerpt: Industrial engineering is a branch of engineering dealing with the optimization of complex processes or systems. It is concerned with the development, improvement, implementation and evaluation of production and service systems. Computational Intelligence Systems find a wide application area in industrial engineering: neural networks in forecasting, fuzzy sets in capital budgeting, ant colony optimization in scheduling, Simulated Annealing in optimization, etc. This book will include most of the application areas of industrial engineering through these computational intelligence systems. In the literature, there is no book including many real and practical applications of Computational Intelligence Systems from the point of view of Industrial Engineering. Every chapter will include explanatory and didactic applications. It is aimed that the book will be a main source for MSc and PhD students.

Progress in Pattern Recognition, Image Analysis and Applications

Author : Alberto Sanfeliu
Publisher : Springer Science & Business Media
ISBN 13 : 3540235272
Total Pages : 720 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis Progress in Pattern Recognition, Image Analysis and Applications by : Alberto Sanfeliu

Download or read book Progress in Pattern Recognition, Image Analysis and Applications written by Alberto Sanfeliu and published by Springer Science & Business Media. This book was released on 2004-10-15 with total page 720 pages. Available in PDF, EPUB and Kindle. Book excerpt: First of all, we want to congratulate two new research communities from M- ico and Brazil that have recently joined the Iberoamerican community and the International Association for Pattern Recognition. We believe that the series of congresses that started as the “Taller Iberoamericano de Reconocimiento de Patrones (TIARP)”, and later became the “Iberoamerican Congress on Pattern Recognition (CIARP)”, has contributed to these groupconsolidatione?orts. We hope that in the near future all the Iberoamerican countries will have their own groups and associations to promote our areas of interest; and that these congresses will serve as the forum for scienti?c research exchange, sharing of - pertise and new knowledge, and establishing contacts that improve cooperation between research groups in pattern recognition and related areas. CIARP 2004 (9th Iberoamerican Congress on Pattern Recognition) was the ninthinaseriesofpioneeringcongressesonpatternrecognitionintheIberoam- ican community. As in the previous year, CIARP 2004 also included worldwide participation. It took place in Puebla, Mexico. The aim of the congress was to promote and disseminate ongoing research and mathematical methods for pattern recognition, image analysis, and applications in such diverse areas as computer vision, robotics, industry, health, entertainment, space exploration, telecommunications, data mining, document analysis,and natural languagep- cessing and recognition, to name a few.

Advances in Self-Organizing Maps

Author : Pablo A. Estévez
Publisher : Springer Science & Business Media
ISBN 13 : 3642352308
Total Pages : 371 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Advances in Self-Organizing Maps by : Pablo A. Estévez

Download or read book Advances in Self-Organizing Maps written by Pablo A. Estévez and published by Springer Science & Business Media. This book was released on 2012-12-14 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Kohonen Maps

Author : E. Oja
Publisher : Elsevier
ISBN 13 : 0080535291
Total Pages : 401 pages
Book Rating : 4.0/5 (85 download)

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Book Synopsis Kohonen Maps by : E. Oja

Download or read book Kohonen Maps written by E. Oja and published by Elsevier. This book was released on 1999-07-02 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Handbook of Natural Computing

Author : Grzegorz Rozenberg
Publisher : Springer
ISBN 13 : 9783540929093
Total Pages : 2052 pages
Book Rating : 4.9/5 (29 download)

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Book Synopsis Handbook of Natural Computing by : Grzegorz Rozenberg

Download or read book Handbook of Natural Computing written by Grzegorz Rozenberg and published by Springer. This book was released on 2012-07-09 with total page 2052 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural Computing is the field of research that investigates both human-designed computing inspired by nature and computing taking place in nature, i.e., it investigates models and computational techniques inspired by nature and also it investigates phenomena taking place in nature in terms of information processing. Examples of the first strand of research covered by the handbook include neural computation inspired by the functioning of the brain; evolutionary computation inspired by Darwinian evolution of species; cellular automata inspired by intercellular communication; swarm intelligence inspired by the behavior of groups of organisms; artificial immune systems inspired by the natural immune system; artificial life systems inspired by the properties of natural life in general; membrane computing inspired by the compartmentalized ways in which cells process information; and amorphous computing inspired by morphogenesis. Other examples of natural-computing paradigms are molecular computing and quantum computing, where the goal is to replace traditional electronic hardware, e.g., by bioware in molecular computing. In molecular computing, data are encoded as biomolecules and then molecular biology tools are used to transform the data, thus performing computations. In quantum computing, one exploits quantum-mechanical phenomena to perform computations and secure communications more efficiently than classical physics and, hence, traditional hardware allows. The second strand of research covered by the handbook, computation taking place in nature, is represented by investigations into, among others, the computational nature of self-assembly, which lies at the core of nanoscience, the computational nature of developmental processes, the computational nature of biochemical reactions, the computational nature of bacterial communication, the computational nature of brain processes, and the systems biology approach to bionetworks where cellular processes are treated in terms of communication and interaction, and, hence, in terms of computation. We are now witnessing exciting interaction between computer science and the natural sciences. While the natural sciences are rapidly absorbing notions, techniques and methodologies intrinsic to information processing, computer science is adapting and extending its traditional notion of computation, and computational techniques, to account for computation taking place in nature around us. Natural Computing is an important catalyst for this two-way interaction, and this handbook is a major record of this important development.

Information and Classification

Author : Otto Opitz
Publisher : Springer Science & Business Media
ISBN 13 : 3642509746
Total Pages : 525 pages
Book Rating : 4.6/5 (425 download)

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Book Synopsis Information and Classification by : Otto Opitz

Download or read book Information and Classification written by Otto Opitz and published by Springer Science & Business Media. This book was released on 2013-03-13 with total page 525 pages. Available in PDF, EPUB and Kindle. Book excerpt: In many fields of science and practice large amounts of data and informationare collected for analyzing and visualizing latent structures as orderings or classifications for example. This volume presents refereed and revised versions of 52 papers selected from the contributions of the 16th AnnualConference of the "German Classification Society". The papers are organized in three major sections on Data Analysis and Classification (1), InformationRetrieval, Knowledge Processing and Software (2), Applications and Special Topics (3). Moreover, the papers were grouped and ordered within the major sections. So, in the first section we find papers on Classification Methods, Fuzzy Classification, Multidimensional Scaling, Discriminant Analysis and Conceptual Analysis. The second section contains papers on Neural Networks and Computational Linguisticsin addition to the mentioned fields. An essential part of the third section attends to Sequence Data and Tree Reconstruction as well as Data Analysis and Informatics in Medicine. As special topics the volume presents applications in Thesauri, Archaeology, Musical Science and Psychometrics.

Pattern Recognition by Self-organizing Neural Networks

Author : Gail A. Carpenter
Publisher : MIT Press
ISBN 13 : 9780262031769
Total Pages : 724 pages
Book Rating : 4.0/5 (317 download)

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Book Synopsis Pattern Recognition by Self-organizing Neural Networks by : Gail A. Carpenter

Download or read book Pattern Recognition by Self-organizing Neural Networks written by Gail A. Carpenter and published by MIT Press. This book was released on 1991 with total page 724 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pattern Recognition by Self-Organizing Neural Networks presentsthe most recent advances in an area of research that is becoming vitally important in the fields ofcognitive science, neuroscience, artificial intelligence, and neural networks in general. The 19articles take up developments in competitive learning and computational maps, adaptive resonancetheory, and specialized architectures and biological connections. Introductorysurvey articles provide a framework for understanding the many models involved in various approachesto studying neural networks. These are followed in Part 2 by articles that form the foundation formodels of competitive learning and computational mapping, and recent articles by Kohonen, applyingthem to problems in speech recognition, and by Hecht-Nielsen, applying them to problems in designingadaptive lookup tables. Articles in Part 3 focus on adaptive resonance theory (ART) networks,selforganizing pattern recognition systems whose top-down template feedback signals guarantee theirstable learning in response to arbitrary sequences of input patterns. In Part 4, articles describeembedding ART modules into larger architectures and provide experimental evidence fromneurophysiology, event-related potentials, and psychology that support the prediction that ARTmechanisms exist in the brain. Contributors: J.-P. Banquet, G.A. Carpenter, S.Grossberg, R. Hecht-Nielsen, T. Kohonen, B. Kosko, T.W. Ryan, N.A. Schmajuk, W. Singer, D. Stork, C.von der Malsburg, C.L. Winter.

Advances in Self-Organizing Maps

Author : Jorma Laaksonen
Publisher : Springer Science & Business Media
ISBN 13 : 3642215653
Total Pages : 380 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Advances in Self-Organizing Maps by : Jorma Laaksonen

Download or read book Advances in Self-Organizing Maps written by Jorma Laaksonen and published by Springer Science & Business Media. This book was released on 2011-06-03 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 8th International Workshop on Self-Organizing Maps, WSOM 2011, held in Espoo, Finland, in June 2011. The 36 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on plenaries; financial and societal applications; theory and methodology; applications of data mining and analysis; language processing and document analysis; and visualization and image processing.

Neural Networks and Deep Learning

Author : Charu C. Aggarwal
Publisher : Springer
ISBN 13 : 3319944630
Total Pages : 512 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Neural Networks and Deep Learning by : Charu C. Aggarwal

Download or read book Neural Networks and Deep Learning written by Charu C. Aggarwal and published by Springer. This book was released on 2018-08-25 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. Why do neural networks work? When do they work better than off-the-shelf machine-learning models? When is depth useful? Why is training neural networks so hard? What are the pitfalls? The book is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems. Applications associated with many different areas like recommender systems, machine translation, image captioning, image classification, reinforcement-learning based gaming, and text analytics are covered. The chapters of this book span three categories: The basics of neural networks: Many traditional machine learning models can be understood as special cases of neural networks. An emphasis is placed in the first two chapters on understanding the relationship between traditional machine learning and neural networks. Support vector machines, linear/logistic regression, singular value decomposition, matrix factorization, and recommender systems are shown to be special cases of neural networks. These methods are studied together with recent feature engineering methods like word2vec. Fundamentals of neural networks: A detailed discussion of training and regularization is provided in Chapters 3 and 4. Chapters 5 and 6 present radial-basis function (RBF) networks and restricted Boltzmann machines. Advanced topics in neural networks: Chapters 7 and 8 discuss recurrent neural networks and convolutional neural networks. Several advanced topics like deep reinforcement learning, neural Turing machines, Kohonen self-organizing maps, and generative adversarial networks are introduced in Chapters 9 and 10. The book is written for graduate students, researchers, and practitioners. Numerous exercises are available along with a solution manual to aid in classroom teaching. Where possible, an application-centric view is highlighted in order to provide an understanding of the practical uses of each class of techniques.

Perspectives of Neural-Symbolic Integration

Author : Barbara Hammer
Publisher : Springer
ISBN 13 : 3540739548
Total Pages : 325 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Perspectives of Neural-Symbolic Integration by : Barbara Hammer

Download or read book Perspectives of Neural-Symbolic Integration written by Barbara Hammer and published by Springer. This book was released on 2007-08-14 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: When it comes to robotics and bioinformatics, the Holy Grail everyone is seeking is how to dovetail logic-based inference and statistical machine learning. This volume offers some possible solutions to this eternal problem. Edited with flair and sensitivity by Hammer and Hitzler, the book contains state-of-the-art contributions in neural-symbolic integration, covering `loose' coupling by means of structure kernels or recursive models as well as `strong' coupling of logic and neural networks.