Detection and Classification of Signals and Noise with Long Memory.

Abstract

Long memory occurs when low frequencies have a fundamental impact on the dependence structure of the data. There may also be high variability which occurs when the data has fat distribution tails. Methods were developed for the detection and classification of signals with such characteristics. Some of these techniques were applied to the analysis of computer traffic. The corresponding article, authored by Leland, Taqqu, Willinger and Wilson, was reprinted a number of times. Its extended version has received the 1995 William J. Bennett Award from the IEEE Communications Society and the 1996 IEEE W.R.G. Baker Prize Award. The Baker Prize Award recognizes 'the most outstanding paper reporting original work' in all publications of the IEEE.

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Document Details

Document Type
Technical Report
Publication Date
Jan 29, 1996
Accession Number
ADA314958

Entities

People

  • Gennady Samorodnitsky
  • Murad S. Taqqu

Organizations

  • Boston University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Brownian Motion
  • Classification
  • Covariance
  • Data Science
  • Detection
  • Gaussian Processes
  • Information Science
  • Knowledge Management
  • Networks
  • Probability
  • Probability Density Functions
  • Random Variables
  • Stationary Processes
  • Statistical Algorithms
  • Statistical Analysis
  • Statistics
  • Stochastic Processes

Readers

  • Computer Networking
  • Military History
  • Radar Systems Engineering.