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Neural Computing for Numeric-to-SymbolicConversion
 

Summary: Neural Computing for
Numeric-to-SymbolicConversion
in
Kevin M. Passino,
ABSTRACT: Neural computing offers mas-
sively parallel computational facilities for the
classification of patterns. In this paper, a cer-
tain type of neural network, called the mul-
tilayer perceptron, is used to classify nu-
meric data and assign appropriate symbols
to various classes. This numeric-to-symbolic
conversion results in a type of "information
extraction," which is similar to what is called
"data reduction" in pattern recognition.
After introducing the idea of using the neural
network as a numeric-to-symbolic converter,
its use in autonomous control is discussed
and several applications are studied. The
perceptron is used as a numeric-to-symbolic
converter for a discrete-event system con-

  

Source: Antsaklis, Panos - Department of Electrical Engineering, University of Notre Dame

 

Collections: Engineering