General Multidecision Theory: Hypothesis Testing and Changepoint Detection with Applications to Homeland Security

Abstract

The objective was to develop general theories of sequential hypothesis testing and quickest change detection for complex multi-population stochastic models, as well as to apply these theories to automatic threat detection and classification with low false alarm and miss-classification rates. More specifically, we addressed complex stochastic models that include: multi-population/multi-channel models; multi-hypothesis scenarios; general stochastic models with non-stationary and dependent observations; prior uncertainty. Within a limited duration of the project (about 8 months) a background for a general theory of testing multiple composite hypotheses was established, and certain particular examples were considered.

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Document Details

Document Type
Technical Report
Publication Date
Oct 06, 2014
Accession Number
ADA618980

Entities

People

  • Alexander G. Tartakovsky

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Cyber
  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Change Detection
  • Computer Networks
  • Data Analysis
  • Department Of Defense
  • Detection
  • Detectors
  • Estimators
  • Homeland Security
  • Mathematics
  • Probability
  • Probability Distributions
  • Random Variables
  • Scientists
  • Sequences
  • Statistics
  • Stochastic Processes
  • Students

Readers

  • Sensor Fusion and Tracking Systems.
  • Statistical inference.