Title :
A neural network methodology for machines´ class identification
Author :
Yacoub, M. ; Bennani, Y.
Author_Institution :
Univ. de Paris-Nord, Villetaneuse, France
Abstract :
Before learning a given machine coded by a set of input-output pair sequences, we are interested in identifying whether this machine is a deterministic finite state machine, and if so whether it is a definite memory machine, a finite memory machine, or has an infinite order. If the result is that it has a finite memory order, we attempt to approximate its input and output memory order. A methodology is proposed, and experiments on different machines are presented
Keywords :
deterministic automata; finite state machines; learning (artificial intelligence); neural nets; class identification; definite memory machine; deterministic finite state machine; finite memory machine; infinite memory machine; input-output pair sequences; neural network methodology; Delay effects; Learning automata; Machine learning; Mathematical model; Neural networks; Recurrent neural networks; Turing machines;
Conference_Titel :
Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
0-7803-4859-1
DOI :
10.1109/IJCNN.1998.682285
