DocumentCode :
907825
Title :
The estimation of the optimum linear decision function with a sequential random method
Author :
Wolff, A.C.
Volume :
12
Issue :
3
fYear :
1966
fDate :
7/1/1966 12:00:00 AM
Firstpage :
312
Lastpage :
315
Abstract :
This paper is concerned with the categorizing of patterns by means of linear decision functions, 
as developed by Highleyman [1], [2]. A new procedure for the estimation of the optimum linear decision function is developed. This procedure determines the minimum estimation of the loss function with a sequential random method. An application of the procedure to the same problem as discussed in [1] and [2] yields better results than the procedure developed by Highleyman.
as developed by Highleyman [1], [2]. A new procedure for the estimation of the optimum linear decision function is developed. This procedure determines the minimum estimation of the loss function with a sequential random method. An application of the procedure to the same problem as discussed in [1] and [2] yields better results than the procedure developed by Highleyman.Keywords :
Pattern classification; Sequential estimation; Appropriate technology; Design methodology; Gradient methods; Instruments; Maximum likelihood estimation; Nuclear physics; Pattern recognition;
fLanguage :
English
Journal_Title :
Information Theory, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/TIT.1966.1053896
Filename :
1053896
Link To Document :
