A New Method for Representing Linguistic Quantifications by Random Sets with Applications to Tracking and Data Fusion

Abstract

There is an obvious need to be able to integrate both linguistic-based and stochastic-based input information in data fusion. In particular, this need is critical in addressing problems of track association, including cyber-state intrusions. This paper treats this issue through a new insight into how three apparently distinct mathematical tools can be combined: "boolean relational event algebra" (BREA), "one point random set coverage representations of fuzzy sets" (OPRSC), and "complexity-reducing algorithm for near optimal fusion" (CRANOF).

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Document Details

Document Type
Technical Report
Publication Date
Jul 08, 2002
Accession Number
ADA506905

Entities

People

  • Donald Bamber
  • Hung T. Nguyen
  • I. R. Goodman
  • William C. Torrez

Organizations

  • Naval Information Warfare Systems Command

Tags

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Boolean Algebra
  • California
  • Data Fusion
  • Fuzzy Logic
  • Fuzzy Sets
  • Intrusion
  • Logic
  • Naval Warfare
  • Navy
  • New Mexico
  • Probability
  • Random Variables
  • Reliability
  • Rhode Island
  • United States
  • War Colleges

Readers

  • Artificial Intelligence
  • Operations Research
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • Cyber
  • Cyber - Cryptography