This book is devoted to adaptive processing of structured information similar to flexible and intelligent information processing by humans - in contrast to merely sequential processing of predominantly symbolic information within a deterministic framework. Adaptive information processing allows for a mixture of sequential and parallel processing of symbolic as well as subsymbolic information within deterministic and probabilistic frameworks. The book originates from a summer school held in September 1997 and thus is ideally suited for advanced courses on adaptive information processing and advanced learning techniques or for self-instruction. Research and design professionals active in the area of neural information processing will find it a valuable state-of-the-art survey.
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First Sentence:
The applications of multilayer perceptron (MLP) architecture to many different application areas, ranging from protein modelling [3], branch instruction prediction in software [6], to rolling steel plant modelling [30], have been very successful. Read the first page Key Phrases - Capitalized Phrases (CAPs): (learn more)
Morgan Kaufmann, New York, International Joint Conference, Englewood Cliffs, San Mateo, International Conference, Prentice Hall, San Francisco, University of Toronto, Connection Science, John Wiley, Parallel Distributed Processing, Academic Press, Automata Theory, College Park, Lecture Notes, Theory of Computing, Computational Learning Theory, Lawrence Erlbaum Associates, Neural Systems, San Diego, Springer Verlag, Stanford University, University of Maryland, Elman-style Recurrent Networks New!
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Front Cover | Table of Contents | First Pages | Back Cover | Surprise Me!
The applications of multilayer perceptron (MLP) architecture to many different application areas, ranging from protein modelling [3], branch instruction prediction in software [6], to rolling steel plant modelling [30], have been very successful. Read the first page Key Phrases - Capitalized Phrases (CAPs): (learn more)
Morgan Kaufmann, New York, International Joint Conference, Englewood Cliffs, San Mateo, International Conference, Prentice Hall, San Francisco, University of Toronto, Connection Science, John Wiley, Parallel Distributed Processing, Academic Press, Automata Theory, College Park, Lecture Notes, Theory of Computing, Computational Learning Theory, Lawrence Erlbaum Associates, Neural Systems, San Diego, Springer Verlag, Stanford University, University of Maryland, Elman-style Recurrent Networks New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Back Cover | Surprise Me!
Citations (learn more)
This book cites 74
books:
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- Advances in Neural Information Processing Systems 12 by Todd K. Leen on 9 pages
- Neural Networks by Gérard Dreyfus on 4 pages
- Introduction to Automata Theory, Languages, and Computation (2nd Edition) by John E. Hopcroft on page 293, page 341, and page 368
- Linear Systems by Thomas Kailath on page 25, page 62, and page 95
- Parallel Distributed Processing: Explorations in the Microstructure of Cognition: Foundations (Volume 1) by James L. McClelland on page 97, and page 167
See all 74 books this book cites
- A Field Guide to Dynamical Recurrent Networks by John F. Kolen in Back Matter
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