Delta-operator based signal processing

Fast algorithms for rapidly sampled data

Research output: Contribution to journalConference article

5 Citations (Scopus)

Abstract

High sampling densities often lead to numerical ill-conditioning in statistical signal processing algorithms. Reformulation of signal or system dynamics via a delta, or divided-difference, dynamical operator can provide a framework within which the amelioration of such ill-conditioning can be treated on a formal and unified basis. A number of basic signal-processing problems have been studied in his context over the past decade, and these are reviewed here.

Original languageEnglish (US)
Pages (from-to)872-877
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
Volume1
StatePublished - Dec 1 1997
EventProceedings of the 1997 36th IEEE Conference on Decision and Control. Part 1 (of 5) - San Diego, CA, USA
Duration: Dec 10 1997Dec 12 1997

Fingerprint

Ill-conditioning
Fast Algorithm
Signal Processing
Mathematical operators
Signal processing
Divided Differences
Operator
Reformulation
System Dynamics
Dynamical systems
Sampling
Context
Framework

All Science Journal Classification (ASJC) codes

  • Safety, Risk, Reliability and Quality
  • Control and Systems Engineering
  • Chemical Health and Safety

Cite this

@article{8ea2b9ae78f5450a8006aa622f6c11f6,
title = "Delta-operator based signal processing: Fast algorithms for rapidly sampled data",
abstract = "High sampling densities often lead to numerical ill-conditioning in statistical signal processing algorithms. Reformulation of signal or system dynamics via a delta, or divided-difference, dynamical operator can provide a framework within which the amelioration of such ill-conditioning can be treated on a formal and unified basis. A number of basic signal-processing problems have been studied in his context over the past decade, and these are reviewed here.",
author = "Poor, {H. Vincent}",
year = "1997",
month = "12",
day = "1",
language = "English (US)",
volume = "1",
pages = "872--877",
journal = "Proceedings of the IEEE Conference on Decision and Control",
issn = "0191-2216",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

Delta-operator based signal processing : Fast algorithms for rapidly sampled data. / Poor, H. Vincent.

In: Proceedings of the IEEE Conference on Decision and Control, Vol. 1, 01.12.1997, p. 872-877.

Research output: Contribution to journalConference article

TY - JOUR

T1 - Delta-operator based signal processing

T2 - Fast algorithms for rapidly sampled data

AU - Poor, H. Vincent

PY - 1997/12/1

Y1 - 1997/12/1

N2 - High sampling densities often lead to numerical ill-conditioning in statistical signal processing algorithms. Reformulation of signal or system dynamics via a delta, or divided-difference, dynamical operator can provide a framework within which the amelioration of such ill-conditioning can be treated on a formal and unified basis. A number of basic signal-processing problems have been studied in his context over the past decade, and these are reviewed here.

AB - High sampling densities often lead to numerical ill-conditioning in statistical signal processing algorithms. Reformulation of signal or system dynamics via a delta, or divided-difference, dynamical operator can provide a framework within which the amelioration of such ill-conditioning can be treated on a formal and unified basis. A number of basic signal-processing problems have been studied in his context over the past decade, and these are reviewed here.

UR - http://www.scopus.com/inward/record.url?scp=0031388338&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0031388338&partnerID=8YFLogxK

M3 - Conference article

VL - 1

SP - 872

EP - 877

JO - Proceedings of the IEEE Conference on Decision and Control

JF - Proceedings of the IEEE Conference on Decision and Control

SN - 0191-2216

ER -