THEORY OF CUMULATIVE DETECTION PROBABILITY

Abstract

Cumulative detection probability, cdp, is defined as probability of at least one success in n trials. 'Success' means that the (signal) stochastic process exceeds a given threshold. Exact formulas or approximations for cdp are given in the cases where the process being sampled in the trials is two-state Markov, Gaussian, 'step, 'and' step-plus-jitter.' In the two-state Markov case, taken largely from others, k-success formulas are also given. Finding cdp is equivalent to finding the distribution of the maximum of a sequence of random variables and to finding a cumulative multivariate distribution.

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Document Details

Document Type
Technical Report
Publication Date
Nov 10, 1964
Accession Number
AD0615497

Entities

People

  • Edward P. Loane
  • Edward S. Boylan
  • Henry R. Richardson

Tags

DTIC Thesaurus Topics

  • Computational Science
  • Data Science
  • Differential Equations
  • Distribution Functions
  • Gaussian Processes
  • Information Science
  • Markov Chains
  • Markov Processes
  • Normal Distribution
  • Probabilistic Models
  • Random Variables
  • Sequences
  • Standards
  • Stationary Processes
  • Statistical Algorithms
  • Stochastic Processes
  • Surveys

Fields of Study

  • Mathematics

Readers

  • Chemistry (specifically Chemical Fluorescence)
  • Statistical inference.