DocumentCode
948238
Title
Exact distribution functions of test length for sequential processors with discrete input data
Author
Proakis, J.
Volume
9
Issue
3
fYear
1963
fDate
7/1/1963 12:00:00 AM
Firstpage
182
Lastpage
191
Abstract
In studies of sequential detection of radar signals, the parameter of primary interest is the length of the sequential test, denoted by
. Since this test length is a random variable, moments and/or probability distribution functions of
are desirable. A procedure is described in this communication for obtaining exact probability distribution functions
and exact average values of
,
, when the input to the sequential processor is discrete radar data (radar data in quantized form). This procedure is based upon the representation of the sequential test as a Markov process. The results are quite general in that they apply to multilevel quantization of the data. However, the procedure appears especially attractive when the number of levels is small as is usually the case when dealing with discrete radar data. The procedure for determining exact distribution functions and average values of
presented herein is compared with the Wald-Girshick approach for obtaining
and
, and the superiority of the former approach in computational convenience is indicated.
. Since this test length is a random variable, moments and/or probability distribution functions of
are desirable. A procedure is described in this communication for obtaining exact probability distribution functions
and exact average values of
,
, when the input to the sequential processor is discrete radar data (radar data in quantized form). This procedure is based upon the representation of the sequential test as a Markov process. The results are quite general in that they apply to multilevel quantization of the data. However, the procedure appears especially attractive when the number of levels is small as is usually the case when dealing with discrete radar data. The procedure for determining exact distribution functions and average values of
presented herein is compared with the Wald-Girshick approach for obtaining
and
, and the superiority of the former approach in computational convenience is indicated.Keywords
Probability functions; Radar detection; Sequential detection; Distributed computing; Distribution functions; Markov processes; Probability distribution; Quantization; Radar detection; Random variables; Sequential analysis; Signal detection; Testing;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/TIT.1963.1057834
Filename
1057834
Link To Document