DocumentCode :
925364
Title :
A general structure for classification
Author :
Sandberg, Irwin W.
Author_Institution :
Dept. of Electr. & Comput. Eng., Texas Univ., Austin, TX, USA
Volume :
40
Issue :
4
fYear :
1993
fDate :
4/1/1993 12:00:00 AM
Firstpage :
288
Lastpage :
289
Abstract :
The problem of classifying signals is considered. Typically, a finite number m of pairwise disjoint sets C1,. . .,Cm of signals is given, and the aim is to synthesize a system that maps the elements of each Cj into a real number aj so that the numbers a1,. . .,am are distinct. A structure that can perform this classification (for any prescribed distinct a1,. . .,am), assuming only that the Cj are compact subsets of a real normed linear space, is presented
Keywords :
pattern recognition; signal detection; classification; compact subsets; pairwise disjoint sets; real normed linear space; signals; Circuits; Feedforward neural networks; Neural networks; Rail to rail inputs; Signal synthesis; Sufficient conditions;
fLanguage :
English
Journal_Title :
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7122
Type :
jour
DOI :
10.1109/81.224307
Filename :
224307
Link To Document :
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