Signal processing models for discrete-time self-similar and multifractal processes

Raghuveer Rao, Seungsin Lee, Erhan Bayraktar, H. Vincent Poor

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations

Abstract

The paper discusses and presents results from recent investigation into three problems. (A) Approaches have previously been developed for describing self-similarity in discrete-time random processes using a discrete-time continuous dilation operator. It is shown here that processes self-similar under this construct, called a discrete-time self-similar system (DTSS), are related to prior discrete-time constructs; specifically they can generate asymptotically second order self-similar processes. (B) The advantage of using long-range prediction of long-range dependent processes is tested. It is shown that for combined long-range and short-range prediction for tracking with a sequence that has bounded increments, long-range prediction does not offer a significant tracking advantage. (C) It is hypothesized that DTSS systems with a time-varying parameter will generate multifractal processes. Empirical results substantiating this surmise are provided.

Original languageEnglish (US)
Pages (from-to)8-12
Number of pages5
JournalConference Record of the Asilomar Conference on Signals, Systems and Computers
Volume1
StatePublished - 2003
EventConference Record of the Thirty-Seventh Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States
Duration: Nov 9 2003Nov 12 2003

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Networks and Communications

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