DocumentCode
1246263
Title
Gradient algorithm for quantization levels in distributed detection systems
Author
Helstrom, Carl W.
Author_Institution
Dept. of Electr. & Comput. Eng., California Univ., San Diego, La Jolla, CA, USA
Volume
31
Issue
1
fYear
1995
Firstpage
390
Lastpage
398
Abstract
An iterative gradient algorithm is presented for determining the quantization levels in each of a number of independent sensors so arranged as to pick up a common signal field. The system is to satisfy the Neyman-Pearson criterion that the probability of detection be maximum for a preassigned false-alarm probability. In general a number of local maxima exist, and the proposed method enables efficient search for these by starting from a variety of initial trial values.<>
Keywords
iterative methods; probability; quantisation (signal); signal detection; Neyman-Pearson criterion; distributed detection systems; initial trial values; iterative gradient algorithm; preassigned false-alarm probability; probability of detection; quantization levels; search; Electromagnetic fields; Iterative algorithms; Probability density function; Quantization; Sensor fusion; Sensor systems; Statistical distributions; Statistics;
fLanguage
English
Journal_Title
Aerospace and Electronic Systems, IEEE Transactions on
Publisher
ieee
ISSN
0018-9251
Type
jour
DOI
10.1109/7.366320
Filename
366320
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