Adaptive processing of sequences and data structures : [second] International Summer School on Neural Networks E.R. Caianiello Vietri sul Mare, Salerno, Italy September 6 13, 1997 : tutorial lectures
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...
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| Körperschaft: | |
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| Weitere Verfasser: | , |
| Format: | Livre numérique |
| Sprache: | Anglais |
| Veröffentlicht: |
Berlin [etc.] :
Springer
[20..].
Cham : Springer Nature |
| Schriftenreihe: | Lecture notes in computer science. Lecture notes in artificial intelligence
1387 |
| Schlagworte: | |
| Online Zugang: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
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Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Adaptive processing of sequences and data structures, International Summer School on Neural Networks "E.R. Caianiello", Vietri sul Mare, Salerno, Italy, Sept. 6-13, 1997, Tutorial Lectures, C. Lee Giles, Marco Gori (eds.), 1998, New York, Springer, 1 vol. (XIV-438 p.), Lecture notes in computer science, 3-540-64341-9 • Adaptive Processing of Sequences and Data Structures, Texte imprimé, 9783662181683 |
Inhaltsangabe:
- Recurrent neural network architectures: An overview
- Gradient based learning methods
- Diagrammatic methods for deriving and relating temporal neural network algorithms
- An introduction to learning structured information
- Neural networks for processing data structures
- The loading problem: Topics in complexity
- Learning dynamic Bayesian networks
- Probabilistic models of neuronal spike trains
- Temporal models in blind source separation
- Recursive neural networks and automata
- The neural network pushdown automaton: Architecture, dynamics and training
- Neural dynamics with stochasticity
- Parsing the stream of time: The value of event-based segmentation in a complex real-world control problem
- Hybrid HMM/ANN systems for speech recognition: Overview and new research directions
- Predictive models for sequence modelling, application to speech and character recognition.