Polynomial interpolation and prediction of continuous-time processes from random samples

Author

Masry, Elias

Author_Institution

Dept. of Electr. & Comput. Eng., California Univ., San Diego, La Jolla, CA, USA

Volume

43

Issue

2

fYear

1997

fDate

3/1/1997 12:00:00 AM

Firstpage

776

Lastpage

783

Abstract

We consider the interpolation and prediction of continuous-time second-order random processes from a finite number of randomly sampled observations using Lagrange polynomial estimators. The sampling process (t₁) is a general stationary point process on the real line. We establish upper bounds on the mean-square interpolation and prediction errors and determine their dependence on the mean sampling rate β and on the number of samples used. Comparisons with the Wiener-Hopf estimator are given

Keywords

continuous time systems; estimation theory; interpolation; polynomials; prediction theory; random processes; signal sampling; stochastic processes; Lagrange polynomial estimators; Wiener-Hopf estimator; continuous-time processes; mean sampling rate; mean-square interpolation; prediction errors; random samples; randomly sampled observations; sampling process; second-order random processes; stationary point process; upper bounds; Fault detection; Inspection; Interpolation; Lagrangian functions; Polynomials; Sampling methods; Sequential analysis; Signal sampling; Statistics; Testing;

fLanguage

English

Journal_Title

Information Theory, IEEE Transactions on

Publisher

ieee

ISSN

0018-9448

Type

jour

DOI

10.1109/18.556139

Filename

556139