In the last two decades the artificial neural networks have been refined and widely used by the researchers and application engineers. We have not witnessed such a large degree of evolution in any other artificial neural network as in the Adaptive Resonance Theory (ART) neural network. The ART network remains plastic, or adaptive, in response to significant events and yet remains stable in response to irrelevant events. This stability-plasticity property is a great step towards realizing intelligent machines capable of autonomous learning in real time environment. The main aim of this book is to report a very small sample of the research on the evolution of ART neural network and its applications. Interested readers may refer literature for many more innovations in ART such as Fuzzy ART, ART2, ART2-a, ARTMAP, ARTMAP-PI, ARTMAP-DS, Gaussian ARTMAP, EXACT ART, and ART-EMAP.
Innovations in ART Neural Networks
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There is a tremendous world-wide interest in the design and applications of artificial neural networks [1] both in universities and in industry. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
familiarity flag, weight rectangles, promoter rules, vigilance criterion, adaptive resonance system, match tracking, prototype node, vigilance parameter, category proliferation, vector presentations, orienting subsystem, incremental supervised learning, promoter data, complement coding, binary input patterns, precursor set, vigilance test, transistor mismatch, winning category, multiple classifier system, rule insertion, input presentation, analog patterns, vigilance level, winning node Key Phrases - Capitalized Phrases (CAPs): (learn more)
United Kingdom, Van Blerkom, International Conference, Academic Press, Image Processing, International Joint Conference, New York, San Diego, San Mateo, Artificial Intelligence, Morgan Kaufmann, Optimized Learning Rate, Probabilistic Neural Network, Receiver Operating Characteristic, Applied Optics, Boston University, Classifier Bayesian, Computer Vision, Multiple Voting, Neural Information Processing Systems, Probabilistic Fuzzy, Technical Report, University of California New!
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Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
There is a tremendous world-wide interest in the design and applications of artificial neural networks [1] both in universities and in industry. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
familiarity flag, weight rectangles, promoter rules, vigilance criterion, adaptive resonance system, match tracking, prototype node, vigilance parameter, category proliferation, vector presentations, orienting subsystem, incremental supervised learning, promoter data, complement coding, binary input patterns, precursor set, vigilance test, transistor mismatch, winning category, multiple classifier system, rule insertion, input presentation, analog patterns, vigilance level, winning node Key Phrases - Capitalized Phrases (CAPs): (learn more)
United Kingdom, Van Blerkom, International Conference, Academic Press, Image Processing, International Joint Conference, New York, San Diego, San Mateo, Artificial Intelligence, Morgan Kaufmann, Optimized Learning Rate, Probabilistic Neural Network, Receiver Operating Characteristic, Applied Optics, Boston University, Classifier Bayesian, Computer Vision, Multiple Voting, Neural Information Processing Systems, Probabilistic Fuzzy, Technical Report, University of California New!
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Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 37
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6
books
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- Pattern Classification (2nd Edition) by Richard O. Duda on page 166, and Back Matter
- Clustering Algorithms (Probability & Mathematical Statistics) by John A. Hartigan on page 129, and Back Matter
- Pattern Recognition with Fuzzy Objective Function Algorithms (Advanced Applications in Pattern Recognition) by James C. Bezdek on page 53, and Back Matter
- Pattern Classification and Scene Analysis by Richard O. Duda on page 166, and Back Matter
- An Introduction to Medical Statistics (Oxford Medical Publications) by Martin Bland on page 188
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- Large Scale Interactive Fuzzy Multiobjective Programming: Decomposition Approaches (Studies in Fuzziness and Soft Computing) by Masatoshi Sakawa in Back Matter
- Visualizing Document Processing: Innovations in Communication Patterns and Textual Forms (Text Translation Computational Processing) by Graziella Tonfoni in Back Matter
- Fuzzy and Neuro-Fuzzy Intelligent Systems (Studies in Fuzziness and Soft Computing) by Ernest Czogala in Back Matter
- Fuzzy and Multiobjective Games for Conflict Resolution (Studies in Fuzziness and Soft Computing) by Ichiro Nishizaki in Front Matter
- Fuzzy Discrete Structures (Studies in Fuzziness and Soft Computing) by Davender S. Malik in Back Matter
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