You have Guest access.
Log In
C. Lee Giles and Marco Gori
Front matter
1-26
Recurrent neural network architectures: An overview
27-62
Gradient based learning methods
63-98
Diagrammatic methods for deriving and relating temporal neural network algorithms
99-120
An introduction to learning structured information
121-144
Neural networks for processing data structures
145-167
The loading problem: Topics in complexity
168-197
Learning dynamic Bayesian networks
198-228
Probabilistic models of neuronal spike trains
229-247
Temporal models in blind source separation
248-295
Recursive neural networks and automata
296-345
The neural network pushdown automaton: Architecture, dynamics and training
346-369
Neural dynamics with stochasticity
370-388
Parsing the stream of time: The value of event-based segmentation in a complex real-world control problem
389-417
Hybrid HMM/ANN systems for speech recognition: Overview and new research directions
418-434
Predictive models for sequence modelling, application to speech and character recognition
Ah Chung Tsoi
Ah Chung Tsoi and Ah Chung Tsoi
Eric A. Wan and Françoise Beaufays
Paolo Frasconi
Alessandro Sperduti
Marco Gori
Zoubin Ghahramani
Pierre Baldi
Lucas C. Parra
Marco Maggini
G. Z. Sun, C. L. Giles and H. H. Chen
Hava T. Siegelmann
Michael C. Mozer and Debra Miller
Hervé Bourlard and Nelson Morgan
P. Gallinari
Frequently asked questions General info on journals and books Send us your feedback Impressum Contact us
© Springer, Part of Springer Science+Business Media Privacy, Disclaimer, Terms & Conditions, and Copyright Info