Prediction and tracking of long-range-dependent sequences

Erhan Bayraktar, H. Vincent Poor, Raghuveer Rao

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Long-range-dependent (LRD) sequences have been found to be of importance in various fields such as telecommunications, signal processing and finance. Since the history of an LRD sequence has significant impact on the present values, it is expected that accurate prediction and tracking of these sequences are easier than of short-range-dependent sequences. The purpose of this paper is to verify whether distant observations in the past might increase the performance of a constrained tracker significantly when this information from the past is used in combination with recent observations.

Original languageEnglish (US)
Pages (from-to)1083-1090
Number of pages8
JournalSystems and Control Letters
Volume54
Issue number11
DOIs
StatePublished - Nov 1 2005

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science(all)
  • Mechanical Engineering
  • Electrical and Electronic Engineering

Keywords

  • Fractional Gaussian noise
  • Long range dependence
  • Tracking problems

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