Dynamic Back-Propagation for Plant Identification and Control
碩士 === 國立交通大學 === 控制工程系 === 82 === While much of the recent emphasis in the connectionist reseaarch has been on feedforward networks with static back- propagation, it is likely that the use of dynamic networks will be of particular importan...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Others |
| Language: | en_US |
| Published: |
1994
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| Online Access: | http://ndltd.ncl.edu.tw/handle/09703957867238072262 |
| Summary: | 碩士 === 國立交通大學 === 控制工程系 === 82 === While much of the recent emphasis in the connectionist
reseaarch has been on feedforward networks with static back-
propagation, it is likely that the use of dynamic networks will
be of particular importance in control-related applications.
This thesis is focused on a learning methodology for recurrent
networks with feedback connections and feedforward networks as
subsystems in a dynamic system. Such a learning methodology is
termed dynamic back-propagation, which is one of the most
prominent learning methods for connectionist networks. A
detailed study of dynamic back-propagation is presented to
provide an insight of the principal ideas that contributed to
the evolution of the concept and the details concerning its
practical applications to identification and control.
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