Statistical analysis of nonparametric transfer function estimates

Author

Guillaume, Patrick ; Kollár, István ; Pintelon, Rik

Author_Institution

Dept. of Fundamental Electr. & Instrum., Vrije Univ., Brussels, Belgium

Volume

45

Issue

2

fYear

1996

fDate

4/1/1996 12:00:00 AM

Firstpage

594

Lastpage

600

Abstract

The Empirical Transfer Function Estimate (ETFE) is the ratio of the Fourier transforms of the output and input signals of a system. It works well when the input signal is deterministic and exactly known. However, when the input signal is random, or it can only be observed with an observation error, the quality of the ETFE deteriorates. Its variance can be infinite even for large signal-to-noise ratios. This is not well known. This paper establishes and analyzes a mathematical model of the ETFE with noisy input signals. It explains the cause of the large variance and suggests modifications which eliminate the above problems

Keywords

Fourier transforms; Monte Carlo methods; estimation theory; measurement theory; random noise; random processes; signal processing; transfer functions; Empirical Transfer Function Estimate; Fourier transforms; Monte Carlo simulation; deterministic input signal; mathematical model; noisy input signals; nonparametric transfer function estimates; observation error; output signals; random signal; signal-to-noise ratio; statistical analysis; variance; Fourier transforms; Frequency estimation; Frequency measurement; Instruments; Mathematical model; Noise measurement; Signal analysis; Signal to noise ratio; Statistical analysis; Transfer functions;

fLanguage

English

Journal_Title

Instrumentation and Measurement, IEEE Transactions on

Publisher

ieee

ISSN

0018-9456

Type

jour

DOI

10.1109/19.492794

Filename

492794