Levy Searches Based on A Priori Information: The Biased Levy Walk

Abstract

Searching for objects with unknown locations based on random walks can be optimized when the walkers obey Levy distributions with a critical exponent. We consider the problem of optimizing statistical searches when a priori information, such as location densities, are known. We consider both spatially dependent exponents and biased search directions. For spatially localized target distributions and non-destructive searches, the search is most improved by biasing the search direction.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2004
Accession Number
ADA638319

Entities

People

  • Andrea Bertozzi
  • Daniel Marthaler
  • Ira B. Schwartz

Organizations

  • University of California, Los Angeles

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Boundaries
  • Brownian Motion
  • Computations
  • Distribution Functions
  • Efficiency
  • Gaussian Distributions
  • Normal Distribution
  • Probability
  • Probability Density Functions
  • Probability Distributions
  • Random Variables
  • Random Walk
  • Simulations
  • Statistics
  • Stochastic Processes
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Sensor Fusion and Tracking Systems.
  • Statistical inference.