Modular Learning in Neural Networks

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Author :
Publisher : Wiley-Interscience
ISBN 13 :
Total Pages : 264 pages
Book Rating : 4.90/5 ( 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.".

Learning and Categorization in Modular Neural Networks

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Author :
Publisher : Psychology Press
ISBN 13 : 1317781376
Total Pages : 257 pages
Book Rating : 4.70/5 ( 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

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Author :
Publisher :
ISBN 13 : 9780745012575
Total Pages : 244 pages
Book Rating : 4.74/5 ( 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 . This book was released on 1992 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Machine Learning with Neural Networks

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Author :
Publisher : Cambridge University Press
ISBN 13 : 1108849563
Total Pages : 262 pages
Book Rating : 4.62/5 ( download)

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Book Synopsis Machine Learning with Neural Networks by : Bernhard Mehlig

Download or read book Machine Learning with Neural Networks written by Bernhard Mehlig and published by Cambridge University Press. This book was released on 2021-10-28 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: This modern and self-contained book offers a clear and accessible introduction to the important topic of machine learning with neural networks. In addition to describing the mathematical principles of the topic, and its historical evolution, strong connections are drawn with underlying methods from statistical physics and current applications within science and engineering. Closely based around a well-established undergraduate course, this pedagogical text provides a solid understanding of the key aspects of modern machine learning with artificial neural networks, for students in physics, mathematics, and engineering. Numerous exercises expand and reinforce key concepts within the book and allow students to hone their programming skills. Frequent references to current research develop a detailed perspective on the state-of-the-art in machine learning research.

Towards Hybrid and Adaptive Computing

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Publisher : Springer Science & Business Media
ISBN 13 : 3642143431
Total Pages : 467 pages
Book Rating : 4.34/5 ( download)

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Book Synopsis Towards Hybrid and Adaptive Computing by : Anupam Shukla

Download or read book Towards Hybrid and Adaptive Computing written by Anupam Shukla and published by Springer Science & Business Media. This book was released on 2010-08-17 with total page 467 pages. Available in PDF, EPUB and Kindle. Book excerpt: Soft Computing today is a very vast field whose extent is beyond measure. This book offers a well structured presentation of the basic concepts of Artificial Neural Networks, Fuzzy Inference Systems and Evolutionary Algorithms.

Springer Handbook of Computational Intelligence

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Author :
Publisher : Springer
ISBN 13 : 3662435055
Total Pages : 1637 pages
Book Rating : 4.52/5 ( download)

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Book Synopsis Springer Handbook of Computational Intelligence by : Janusz Kacprzyk

Download or read book Springer Handbook of Computational Intelligence written by Janusz Kacprzyk and published by Springer. This book was released on 2015-05-28 with total page 1637 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Springer Handbook for Computational Intelligence is the first book covering the basics, the state-of-the-art and important applications of the dynamic and rapidly expanding discipline of computational intelligence. This comprehensive handbook makes readers familiar with a broad spectrum of approaches to solve various problems in science and technology. Possible approaches include, for example, those being inspired by biology, living organisms and animate systems. Content is organized in seven parts: foundations; fuzzy logic; rough sets; evolutionary computation; neural networks; swarm intelligence and hybrid computational intelligence systems. Each Part is supervised by its own Part Editor(s) so that high-quality content as well as completeness are assured.

Learning and Categorization in Modular Neural Networks

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Author :
Publisher : Psychology Press
ISBN 13 : 1317781368
Total Pages : 261 pages
Book Rating : 4.63/5 ( 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 261 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.

Combining Artificial Neural Nets

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Author :
Publisher : Springer Science & Business Media
ISBN 13 : 1447107934
Total Pages : 300 pages
Book Rating : 4.34/5 ( download)

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Book Synopsis Combining Artificial Neural Nets by : Amanda J.C. Sharkey

Download or read book Combining Artificial Neural Nets written by Amanda J.C. Sharkey and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume, written by leading researchers, presents methods of combining neural nets to improve their performance. The techniques include ensemble-based approaches, where a variety of methods are used to create a set of different nets trained on the same task, and modular approaches, where a task is decomposed into simpler problems. The techniques are also accompanied by an evaluation of their relative effectiveness and their application to a variety of problems.

Biomimetic Neural Learning for Intelligent Robots

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Author :
Publisher : Springer
ISBN 13 : 3540318968
Total Pages : 390 pages
Book Rating : 4.65/5 ( download)

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Book Synopsis Biomimetic Neural Learning for Intelligent Robots by : Stefan Wermter

Download or read book Biomimetic Neural Learning for Intelligent Robots written by Stefan Wermter and published by Springer. This book was released on 2005-08-25 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: This state-of-the-art survey contains selected papers contributed by researchers in intelligent systems, cognitive robotics, and neuroscience including contributions from the MirrorBot project and from the NeuroBotics Workshop 2004. The research work presented demonstrates significant novel developments in biologically inspired neural models for use in intelligent robot environments and biomimetic cognitive behavior.

Proceedings of the Winter, 1990, International Joint Conference on Neural Networks

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Author :
Publisher : Taylor & Francis
ISBN 13 : 1317728335
Total Pages : 1588 pages
Book Rating : 4.37/5 ( download)

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Book Synopsis Proceedings of the Winter, 1990, International Joint Conference on Neural Networks by : Maureen Caudill

Download or read book Proceedings of the Winter, 1990, International Joint Conference on Neural Networks written by Maureen Caudill and published by Taylor & Francis. This book was released on 2022-03-10 with total page 1588 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two volume set provides the complete proceedings of the 1990 International Joint Conference on Neural Networks held in Washington, D.C. Complete with subject, author, and title indices, it provides an invaluable reference to the current state-of-the-art in neural networks. Included in this volume are the latest research results, applications, and products from over 2,000 researchers and application developers from around the world. Ideal as a reference for researchers and practitioners of neuroscience, the two volumes are divided into eight sections: * Neural and Cognitive Sciences * Pattern Recognition and Analysis of Network Dynamics * Learning Theory * Plenary Lecture by Bernard Widrow * Special Lectures on Self-Organizing Neural Architectures * Application Systems and Network Implementations * Robotics, Speech, Signal Processing, and Vision * Expert Systems and Other Real-World Applications