Learning And Categorization In Modular Neural Networks

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Learning and Categorization in Modular Neural Networks

Author : Jacob M.J. Murre
Publisher : Psychology Press
ISBN 13 : 1317781376
Total Pages : 257 pages
Book Rating : 4.3/5 (177 download)

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Book Synopsis Learning and Categorization in Modular Neural Networks by : Jacob M.J. Murre

Download or read book Learning and Categorization in Modular Neural Networks written by Jacob M.J. Murre and published by Psychology Press. This book was released on 2014-02-25 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces a new neural network model called CALM, for categorization and learning in neural networks. The author demonstrates how this model can learn the word superiority effect for letter recognition, and discusses a series of studies that simulate experiments in implicit and explicit memory, involving normal and amnesic patients. Pathological, but psychologically accurate, behavior is produced by "lesioning" the arousal system of these models. A concise introduction to genetic algorithms, a new computing method based on the biological metaphor of evolution, and a demonstration on how these algorithms can design network architectures with superior performance are included in this volume. The role of modularity in parallel hardware and software implementations is considered, including transputer networks and a dedicated 400-processor neurocomputer built by the developers of CALM in cooperation with Delft Technical University. Concluding with an evaluation of the psychological and biological plausibility of CALM models, the book offers a general discussion of catastrophic interference, generalization, and representational capacity of modular neural networks. Researchers in cognitive science, neuroscience, computer simulation sciences, parallel computer architectures, and pattern recognition will be interested in this volume, as well as anyone engaged in the study of neural networks, neurocomputers, and neurosimulators.

Learning and Categorization in Modular Neural Networks

Author : Jacob Murre
Publisher : Psychology Press
ISBN 13 : 9780805813388
Total Pages : 244 pages
Book Rating : 4.8/5 (133 download)

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Book Synopsis Learning and Categorization in Modular Neural Networks by : Jacob Murre

Download or read book Learning and Categorization in Modular Neural Networks written by Jacob Murre and published by Psychology Press. This book was released on 1992 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces a new neural network model called CALM, for categorization and learning in neural networks. The author demonstrates how this model can learn the word superiority effect for letter recognition, and discusses a series of studies that simulate experiments in implicit and explicit memory, involving normal and amnesic patients. Pathological, but psychologically accurate, behavior is produced by "lesioning" the arousal system of these models. A concise introduction to genetic algorithms, a new computing method based on the biological metaphor of evolution, and a demonstration on how these algorithms can design network architectures with superior performance are included in this volume. The role of modularity in parallel hardware and software implementations is considered, including transputer networks and a dedicated 400-processor neurocomputer built by the developers of CALM in cooperation with Delft Technical University. Concluding with an evaluation of the psychological and biological plausibility of CALM models, the book offers a general discussion of catastrophic interference, generalization, and representational capacity of modular neural networks. Researchers in cognitive science, neuroscience, computer simulation sciences, parallel computer architectures, and pattern recognition will be interested in this volume, as well as anyone engaged in the study of neural networks, neurocomputers, and neurosimulators.

New Classification Method Based on Modular Neural Networks with the LVQ Algorithm and Type-2 Fuzzy Logic

Author : Jonathan Amezcua
Publisher : Springer
ISBN 13 : 3319737732
Total Pages : 78 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis New Classification Method Based on Modular Neural Networks with the LVQ Algorithm and Type-2 Fuzzy Logic by : Jonathan Amezcua

Download or read book New Classification Method Based on Modular Neural Networks with the LVQ Algorithm and Type-2 Fuzzy Logic written by Jonathan Amezcua and published by Springer. This book was released on 2018-02-05 with total page 78 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book a new model for data classification was developed. This new model is based on the competitive neural network Learning Vector Quantization (LVQ) and type-2 fuzzy logic. This computational model consists of the hybridization of the aforementioned techniques, using a fuzzy logic system within the competitive layer of the LVQ network to determine the shortest distance between a centroid and an input vector. This new model is based on a modular LVQ architecture to further improve its performance on complex classification problems. It also implements a data-similarity process for preprocessing the datasets, in order to build dynamic architectures, having the classes with the highest degree of similarity in different modules. Some architectures were developed in order to work mainly with two datasets, an arrhythmia dataset (using ECG signals) for classifying 15 different types of arrhythmias, and a satellite images segments dataset used for classifying six different types of soil. Both datasets show interesting features that makes them interesting for testing new classification methods.

Modular Learning in Neural Networks

Author : Tomas Hrycej
Publisher : Wiley-Interscience
ISBN 13 :
Total Pages : 264 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Modular Learning in Neural Networks by : Tomas Hrycej

Download or read book Modular Learning in Neural Networks written by Tomas Hrycej and published by Wiley-Interscience. This book was released on 1992-10-09 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Modular Learning in Neural Networks covers the full range of conceivable approaches to the modularization of learning, including decomposition of learning into modules using supervised and unsupervised learning types; decomposition of the function to be mapped into linear and nonlinear parts; decomposition of the neural network to minimize harmful interferences between a large number of network parameters during learning; decomposition of the application task into subtasks that are learned separately; decomposition into a knowledge-based part and a learning part. The book attempts to show that modular learning based on these approaches is helpful in improving the learning performance of neural networks. It demonstrates this by applying modular methods to a pair of benchmark cases - a medical classification problem of realistic size, encompassing 7,200 cases of thyroid disorder; and a handwritten digits classification problem, involving several thousand cases. In so doing, the book shows that some of the proposed methods lead to substantial improvements in solution quality and learning speed, as well as enhanced robustness with regard to learning control parameters.".

Predictive Modular Neural Networks

Author : Vassilios Petridis
Publisher : Springer Science & Business Media
ISBN 13 : 9780792382904
Total Pages : 336 pages
Book Rating : 4.3/5 (829 download)

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Book Synopsis Predictive Modular Neural Networks by : Vassilios Petridis

Download or read book Predictive Modular Neural Networks written by Vassilios Petridis and published by Springer Science & Business Media. This book was released on 1998-09-30 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: The subject of this book is predictive modular neural networks and their ap plication to time series problems: classification, prediction and identification. The intended audience is researchers and graduate students in the fields of neural networks, computer science, statistical pattern recognition, statistics, control theory and econometrics. Biologists, neurophysiologists and medical engineers may also find this book interesting. In the last decade the neural networks community has shown intense interest in both modular methods and time series problems. Similar interest has been expressed for many years in other fields as well, most notably in statistics, control theory, econometrics etc. There is a considerable overlap (not always recognized) of ideas and methods between these fields. Modular neural networks come by many other names, for instance multiple models, local models and mixtures of experts. The basic idea is to independently develop several "subnetworks" (modules), which may perform the same or re lated tasks, and then use an "appropriate" method for combining the outputs of the subnetworks. Some of the expected advantages of this approach (when compared with the use of "lumped" or "monolithic" networks) are: superior performance, reduced development time and greater flexibility. For instance, if a module is removed from the network and replaced by a new module (which may perform the same task more efficiently), it should not be necessary to retrain the aggregate network.

Artificial Neural Networks, 2

Author : I. Aleksander
Publisher : Elsevier
ISBN 13 : 148329806X
Total Pages : 879 pages
Book Rating : 4.4/5 (832 download)

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Book Synopsis Artificial Neural Networks, 2 by : I. Aleksander

Download or read book Artificial Neural Networks, 2 written by I. Aleksander and published by Elsevier. This book was released on 2014-06-28 with total page 879 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume proceedings compilation is a selection of research papers presented at the ICANN-92. The scope of the volumes is interdisciplinary, ranging from the minutiae of VLSI hardware, to new discoveries in neurobiology, through to the workings of the human mind. USA and European research is well represented, including not only new thoughts from old masters but also a large number of first-time authors who are ensuring the continued development of the field.

Categorization and learning in neural networks

Author : Jacob M. Murre
Publisher :
ISBN 13 :
Total Pages : 306 pages
Book Rating : 4.:/5 (654 download)

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Book Synopsis Categorization and learning in neural networks by : Jacob M. Murre

Download or read book Categorization and learning in neural networks written by Jacob M. Murre and published by . This book was released on 1992 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Artificial Neural Networks - ICANN 2007

Author : Joaquim Marques de Sá
Publisher : Springer
ISBN 13 : 3540746900
Total Pages : 999 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Artificial Neural Networks - ICANN 2007 by : Joaquim Marques de Sá

Download or read book Artificial Neural Networks - ICANN 2007 written by Joaquim Marques de Sá and published by Springer. This book was released on 2007-09-14 with total page 999 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the first of a two-volume set that constitutes the refereed proceedings of the 17th International Conference on Artificial Neural Networks, ICANN 2007, held in Porto, Portugal, September 2007. Coverage includes advances in neural network learning methods, advances in neural network architectures, neural dynamics and complex systems, data analysis, evolutionary computing, agents learning, as well as temporal synchronization and nonlinear dynamics in neural networks.

Advances in Neural Networks - ISNN 2006

Author : Jun Wang
Publisher : Springer Science & Business Media
ISBN 13 : 3540344829
Total Pages : 1429 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Advances in Neural Networks - ISNN 2006 by : Jun Wang

Download or read book Advances in Neural Networks - ISNN 2006 written by Jun Wang and published by Springer Science & Business Media. This book was released on 2006-05-11 with total page 1429 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is Volume III of a three volume set constituting the refereed proceedings of the Third International Symposium on Neural Networks, ISNN 2006. 616 revised papers are organized in topical sections on neurobiological analysis, theoretical analysis, neurodynamic optimization, learning algorithms, model design, kernel methods, data preprocessing, pattern classification, computer vision, image and signal processing, system modeling, robotic systems, transportation systems, communication networks, information security, fault detection, financial analysis, bioinformatics, biomedical and industrial applications, and more.

Artificial Neural Networks

Author : Kenji Suzuki
Publisher : BoD – Books on Demand
ISBN 13 : 9535109359
Total Pages : 268 pages
Book Rating : 4.5/5 (351 download)

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Book Synopsis Artificial Neural Networks by : Kenji Suzuki

Download or read book Artificial Neural Networks written by Kenji Suzuki and published by BoD – Books on Demand. This book was released on 2013-01-16 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural networks may probably be the single most successful technology in the last two decades which has been widely used in a large variety of applications. The purpose of this book is to provide recent advances of architectures, methodologies, and applications of artificial neural networks. The book consists of two parts: the architecture part covers architectures, design, optimization, and analysis of artificial neural networks; the applications part covers applications of artificial neural networks in a wide range of areas including biomedical, industrial, physics, and financial applications. Thus, this book will be a fundamental source of recent advances and applications of artificial neural networks. The target audience of this book includes college and graduate students, and engineers in companies.

Modular Neural Networks and Type-2 Fuzzy Systems for Pattern Recognition

Author : Patricia Melin
Publisher : Springer Science & Business Media
ISBN 13 : 3642241387
Total Pages : 216 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Modular Neural Networks and Type-2 Fuzzy Systems for Pattern Recognition by : Patricia Melin

Download or read book Modular Neural Networks and Type-2 Fuzzy Systems for Pattern Recognition written by Patricia Melin and published by Springer Science & Business Media. This book was released on 2011-10-18 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes hybrid intelligent systems using type-2 fuzzy logic and modular neural networks for pattern recognition applications. Hybrid intelligent systems combine several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful pattern recognition systems. Type-2 fuzzy logic is an extension of traditional type-1 fuzzy logic that enables managing higher levels of uncertainty in complex real world problems, which are of particular importance in the area of pattern recognition. The book is organized in three main parts, each containing a group of chapters built around a similar subject. The first part consists of chapters with the main theme of theory and design algorithms, which are basically chapters that propose new models and concepts, which are the basis for achieving intelligent pattern recognition. The second part contains chapters with the main theme of using type-2 fuzzy models and modular neural networks with the aim of designing intelligent systems for complex pattern recognition problems, including iris, ear, face and voice recognition. The third part contains chapters with the theme of evolutionary optimization of type-2 fuzzy systems and modular neural networks in the area of intelligent pattern recognition, which includes the application of genetic algorithms for obtaining optimal type-2 fuzzy integration systems and ideal neural network architectures for solving problems in this area.

World Congress on Neural Networks

Author : Paul Werbos
Publisher : Routledge
ISBN 13 : 1317713427
Total Pages : 860 pages
Book Rating : 4.3/5 (177 download)

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Book Synopsis World Congress on Neural Networks by : Paul Werbos

Download or read book World Congress on Neural Networks written by Paul Werbos and published by Routledge. This book was released on 2021-09-09 with total page 860 pages. Available in PDF, EPUB and Kindle. Book excerpt: Centered around 20 major topic areas of both theoretical and practical importance, the World Congress on Neural Networks provides its registrants -- from a diverse background encompassing industry, academia, and government -- with the latest research and applications in the neural network field.

Advances in Neural Networks - ISNN 2005

Author : Jun Wang
Publisher : Springer
ISBN 13 : 3540320679
Total Pages : 994 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Advances in Neural Networks - ISNN 2005 by : Jun Wang

Download or read book Advances in Neural Networks - ISNN 2005 written by Jun Wang and published by Springer. This book was released on 2005-05-04 with total page 994 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book and its sister volumes constitute the proceedings of the 2nd International Symposium on Neural Networks (ISNN 2005). ISNN 2005 was held in the beautiful mountain city Chongqing by the upper Yangtze River in southwestern China during May 30–June 1, 2005, as a sequel of ISNN 2004 successfully held in Dalian, China. ISNN emerged as a leading conference on neural computation in the region with - creasing global recognition and impact. ISNN 2005 received 1425 submissions from authors on ?ve continents (Asia, Europe, North America, South America, and Oc- nia), 33 countries and regions (Mainland China, Hong Kong, Macao, Taiwan, South Korea, Japan, Singapore, Thailand, India, Nepal, Iran, Qatar, United Arab Emirates, Turkey, Lithuania, Hungary, Poland, Austria, Switzerland, Germany, France, Sweden, Norway, Spain, Portugal, UK, USA, Canada, Venezuela, Brazil, Chile, Australia, and New Zealand). Based on rigorous reviews, 483 high-quality papers were selected by the Program Committee for presentation at ISNN 2005 and publication in the proce- ings, with an acceptance rate of less than 34%. In addition to the numerous contributed papers, 10 distinguished scholars were invited to give plenary speeches and tutorials at ISNN 2005.

Neural Networks

Author : G David Garson
Publisher : SAGE
ISBN 13 : 0857026275
Total Pages : 201 pages
Book Rating : 4.8/5 (57 download)

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Book Synopsis Neural Networks by : G David Garson

Download or read book Neural Networks written by G David Garson and published by SAGE. This book was released on 1998-09-24 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the first accessible introduction to neural network analysis as a methodological strategy for social scientists. The author details numerous studies and examples which illustrate the advantages of neural network analysis over other quantitative and modelling methods in widespread use. Methods are presented in an accessible style for readers who do not have a background in computer science. The book provides a history of neural network methods, a substantial review of the literature, detailed applications, coverage of the most common alternative models and examples of two leading software packages for neural network analysis.

Handbook of Pattern Recognition and Computer Vision

Author : Chi-hau Chen
Publisher : World Scientific
ISBN 13 : 9814273384
Total Pages : 797 pages
Book Rating : 4.8/5 (142 download)

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Book Synopsis Handbook of Pattern Recognition and Computer Vision by : Chi-hau Chen

Download or read book Handbook of Pattern Recognition and Computer Vision written by Chi-hau Chen and published by World Scientific. This book was released on 2010 with total page 797 pages. Available in PDF, EPUB and Kindle. Book excerpt: Both pattern recognition and computer vision have experienced rapid progress in the last twenty-five years. This book provides the latest advances on pattern recognition and computer vision along with their many applications. It features articles written by renowned leaders in the field while topics are presented in readable form to a wide range of readers. The book is divided into five parts: basic methods in pattern recognition, basic methods in computer vision and image processing, recognition applications, life science and human identification, and systems and technology. There are eight new chapters on the latest developments in life sciences using pattern recognition as well as two new chapters on pattern recognition in remote sensing.

Proceedings of the Fourteenth Annual Conference of the Cognitive Science Society

Author : Cognitive Science Society (US) Conference
Publisher : Psychology Press
ISBN 13 : 1317781600
Total Pages : 1212 pages
Book Rating : 4.3/5 (177 download)

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Book Synopsis Proceedings of the Fourteenth Annual Conference of the Cognitive Science Society by : Cognitive Science Society (US) Conference

Download or read book Proceedings of the Fourteenth Annual Conference of the Cognitive Science Society written by Cognitive Science Society (US) Conference and published by Psychology Press. This book was released on 2014-05-12 with total page 1212 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume features the complete text of all regular papers, posters, and summaries of symposia presented at the 14th annual meeting of the Cognitive Science Society.

Hierarchical Modular Granular Neural Networks with Fuzzy Aggregation

Author : Daniela Sanchez
Publisher : Springer
ISBN 13 : 3319288628
Total Pages : 107 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Hierarchical Modular Granular Neural Networks with Fuzzy Aggregation by : Daniela Sanchez

Download or read book Hierarchical Modular Granular Neural Networks with Fuzzy Aggregation written by Daniela Sanchez and published by Springer. This book was released on 2016-02-23 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, a new method for hybrid intelligent systems is proposed. The proposed method is based on a granular computing approach applied in two levels. The techniques used and combined in the proposed method are modular neural networks (MNNs) with a Granular Computing (GrC) approach, thus resulting in a new concept of MNNs; modular granular neural networks (MGNNs). In addition fuzzy logic (FL) and hierarchical genetic algorithms (HGAs) are techniques used in this research work to improve results. These techniques are chosen because in other works have demonstrated to be a good option, and in the case of MNNs and HGAs, these techniques allow to improve the results obtained than with their conventional versions; respectively artificial neural networks and genetic algorithms.