Learning with Recurrent Neural Networks
Folding networks, a generalisation of recurrent neural networks to tree structured inputs, are investigated as a mechanism to learn regularities on classical symbolic data, for example. The architecture, the training mechanism, and several applications in different areas are explained. Afterwards a...
Κύριος συγγραφέας: | Hammer, Barbara (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut) |
---|---|
Συγγραφή απο Οργανισμό/Αρχή: | SpringerLink (Online service) |
Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
Γλώσσα: | English |
Έκδοση: |
London :
Springer London : Imprint: Springer,
2000.
|
Έκδοση: | 1st ed. 2000. |
Σειρά: | Lecture Notes in Control and Information Sciences,
254 |
Θέματα: | |
Διαθέσιμο Online: | Full Text via HEAL-Link |
Παρόμοια τεκμήρια
-
Control of Flexible-link Manipulators Using Neural Networks
ανά: Talebi, H.A, κ.ά.
Έκδοση: (2001) -
Learning, Control and Hybrid Systems Festschrift in honor of Bruce Allen Francis and Mathukumalli Vidyasagar on the occasion of their 50th birthdays /
Έκδοση: (1999) -
Flexible-link Robot Manipulators Control Techniques and Structural Design /
ανά: Moallem, M., κ.ά.
Έκδοση: (2000) -
Experimental Robotics IV The 4th International Symposium, Stanford, California, June 30 - July 2, 1995 /
Έκδοση: (1997) -
Finite-Spectrum Assignment for Time-Delay Systems
ανά: Wang, Qing-Guo, κ.ά.
Έκδοση: (1999)