Adaptive Signal Detection with Finite Memory

Published

Journal Article

The purpose of this presentation is to develop and evaluate an algorithm for determining a finite memory detector applicable to statistical signal detection theory. In the Bayesian signal detection theory, infinite soft or changeable memory is tacitly assumed. Since an infinite memory is physically unrealizable, this study postulates a finite memory scheme which is applicable to a large class of signal detection problems. A general sequentially operating finite memory detector design is obtained and then evaluated for the signal known exactly and the signal known except amplitude problems. Detection performance as a function of memory size is presented for finite observation records using the receiver operating characteristic and plots of probability of decision error versus time. These results show the tradeoff between memory size and processing time to achieve a given detection performance. An important result is that for finite sample records a small finite memory detector with a memory size on the order of 7 states, i.e., a 3-bit computer word, yields detection performance very near that of the optimuminfinite memory detector. Copyright © 1972 by The Institute of Electrical and Electronics Engineers, Inc.

Full Text

Duke Authors

Cited Authors

  • Baxa, EG; Nolte, LW

Published Date

  • January 1, 1972

Published In

Volume / Issue

  • SMC-2 / 1

Start / End Page

  • 42 - 49

Electronic International Standard Serial Number (EISSN)

  • 2168-2909

International Standard Serial Number (ISSN)

  • 0018-9472

Digital Object Identifier (DOI)

  • 10.1109/TSMC.1972.5408555

Citation Source

  • Scopus