| Autor: |
Gabrijel I; Faculty of Computer and Information Science, University of Ljubljana, Trzaska c. 25, SI-1001, Ljubljana, Slovenia. ivan.gabrijel@fri.uni-lj.si, Dobnikar A |
| Jazyk: |
angličtina |
| Zdroj: |
Neural networks : the official journal of the International Neural Network Society [Neural Netw] 2003 Jan; Vol. 16 (1), pp. 101-20. |
| DOI: |
10.1016/s0893-6080(02)00221-6 |
| Abstrakt: |
In this paper finite automata are treated as general discrete dynamical systems from the viewpoint of systems theory. The unconditional on-line identification of an unknown finite automaton is the problem considered. A generalized architecture of recurrent neural networks with a corresponding on-line learning scheme is proposed as a solution to the problem. An on-line rule-extraction algorithm is further introduced. The architecture presented, the on-line learning scheme and the on-line rule-extraction method are tested on different, strongly connected automata, ranging from a very simple example with two states only to a more interesting and complex one with 64 states; the results of both training and extraction processes are very promising. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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