Noise-assisted data processing in measurement science: Part two

Author

Yan, Ruqiang ; Zhao, Rui ; Gao, Robert X.

Author_Institution

Instrum. Sci. & Technol., Southeast Univ., Nanjing, China

Volume

15

Issue

6

fYear

2012

fDate

12/1/2012 12:00:00 AM

Firstpage

32

Lastpage

35

Abstract

In Part One of this tutorial [1], we introduced stochastic resonance-based data processing, where a weak signal can be amplified and detected by deliberately adding a small amount of noise to a nonlinear bistable or multi-stable system. In this part of the tutorial, we introduce another noise-assisted data processing technique, ensemble empirical mode decomposition (EEMD), which has attracted increasing attention in various science and engineering domains including measurement science.

Keywords

data analysis; measurement systems; signal denoising; signal detection; singular value decomposition; stochastic processes; EEMD; ensemble empirical mode decomposition; measurement science; noise assisted data processing; nonlinear bistable system; nonlinear multistable system; signal amplification; signal detection; stochastic resonance-based data processing; Noise measurement; Process control; Resonance; Stochastic resonance; Tutorials; White noise;

fLanguage

English

Journal_Title

Instrumentation & Measurement Magazine, IEEE

Publisher

ieee

ISSN

1094-6969

Type

jour

DOI

10.1109/MIM.2012.6365542

Filename

6365542