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 /
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 / [electronic resource] :
edited by C.Lee Giles, Marco Gori.
- 1st ed. 1998.
- XIV, 438 p. online resource.
- Lecture Notes in Artificial Intelligence, 1387 2945-9141 ; .
- Lecture Notes in Artificial Intelligence, 1387 .
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.
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.
9783540697527
10.1007/BFb0053992 doi
Computer systems.
Computer programming.
Artificial intelligence.
Computer science.
Microprocessors.
Computer architecture.
Artificial intelligence--Data processing.
Computer System Implementation.
Programming Techniques.
Artificial Intelligence.
Theory of Computation.
Processor Architectures.
Data Science.
QA76.9.S88
004.2
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.
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.
9783540697527
10.1007/BFb0053992 doi
Computer systems.
Computer programming.
Artificial intelligence.
Computer science.
Microprocessors.
Computer architecture.
Artificial intelligence--Data processing.
Computer System Implementation.
Programming Techniques.
Artificial Intelligence.
Theory of Computation.
Processor Architectures.
Data Science.
QA76.9.S88
004.2