Adaptive Processing of Sequences and Data Structures (häftad)
Format
Häftad (Paperback / softback)
Språk
Engelska
Antal sidor
438
Utgivningsdatum
1998-03-01
Upplaga
1998 ed.
Förlag
Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Medarbetare
Giles, C. Lee (ed.), Gori, Marco (ed.)
Illustratör/Fotograf
Illustrations
Illustrationer
XIV, 438 p.
Dimensioner
234 x 156 x 23 mm
Vikt
627 g
Antal komponenter
1
Komponenter
1 Paperback / softback
ISBN
9783540643418
Adaptive Processing of Sequences and Data Structures (häftad)

Adaptive Processing of Sequences and Data Structures

International Summer School on Neural Networks, "E.R. Caianiello", Vietri sul Mare, Salerno, Italy, September 6-13, 1997, Tutorial Lectures

Häftad Engelska, 1998-03-01
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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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Innehållsförteckning

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.