Nonlinear signal processing and system identification: applications to time series from electrochemical reactions

J. L. Hudson; M. Kube; R. A. Adomaitis; I. G. Kevrekidis; A. S. Lapedes; R. M. Farber

doi:10.1016/0009-2509(90)80079-T

Nonlinear signal processing and system identification: applications to time series from electrochemical reactions

J. L. Hudson, M. Kube, R. A. Adomaitis, I. G. Kevrekidis, A. S. Lapedes, R. M. Farber

Chemical & Biological Engineering

Research output: Contribution to journal › Article › peer-review

55 Scopus citations

Abstract

We show how nonlinear signal processing techniques can be used for extracting simple dynamic models from complex experimental time series. A neural network analysis is applied to measurements of current versus time from an experimental system where the electrodissolution of copper in a phosphoric acid solution takes place. We investigate transitions from steady to oscillatory behavior and from period-one to period-two oscillations. Such procedures can be used in the analysis of systems for which no adequate phenomenological models exist.

Original language	English (US)
Pages (from-to)	2075-2081
Number of pages	7
Journal	Chemical Engineering Science
Volume	45
Issue number	8
DOIs	https://doi.org/10.1016/0009-2509(90)80079-T
State	Published - 1990

All Science Journal Classification (ASJC) codes

General Chemistry
General Chemical Engineering
Industrial and Manufacturing Engineering

Keywords

Bifurcations
Electrochemical Oscillations
Neural Networks
Nonlinear Dynamics
Signal Processing

Access to Document

10.1016/0009-2509(90)80079-T

Cite this

@article{f10341848c4746c9a7a9ba68e97cf615,

title = "Nonlinear signal processing and system identification: applications to time series from electrochemical reactions",

abstract = "We show how nonlinear signal processing techniques can be used for extracting simple dynamic models from complex experimental time series. A neural network analysis is applied to measurements of current versus time from an experimental system where the electrodissolution of copper in a phosphoric acid solution takes place. We investigate transitions from steady to oscillatory behavior and from period-one to period-two oscillations. Such procedures can be used in the analysis of systems for which no adequate phenomenological models exist.",

keywords = "Bifurcations, Electrochemical Oscillations, Neural Networks, Nonlinear Dynamics, Signal Processing",

author = "Hudson, \{J. L.\} and M. Kube and Adomaitis, \{R. A.\} and Kevrekidis, \{I. G.\} and Lapedes, \{A. S.\} and Farber, \{R. M.\}",

year = "1990",

doi = "10.1016/0009-2509(90)80079-T",

language = "English (US)",

volume = "45",

pages = "2075--2081",

journal = "Chemical Engineering Science",

issn = "0009-2509",

publisher = "Elsevier B.V.",

number = "8",

}

TY - JOUR

T1 - Nonlinear signal processing and system identification

T2 - applications to time series from electrochemical reactions

AU - Hudson, J. L.

AU - Kube, M.

AU - Adomaitis, R. A.

AU - Kevrekidis, I. G.

AU - Lapedes, A. S.

AU - Farber, R. M.

PY - 1990

Y1 - 1990

N2 - We show how nonlinear signal processing techniques can be used for extracting simple dynamic models from complex experimental time series. A neural network analysis is applied to measurements of current versus time from an experimental system where the electrodissolution of copper in a phosphoric acid solution takes place. We investigate transitions from steady to oscillatory behavior and from period-one to period-two oscillations. Such procedures can be used in the analysis of systems for which no adequate phenomenological models exist.

AB - We show how nonlinear signal processing techniques can be used for extracting simple dynamic models from complex experimental time series. A neural network analysis is applied to measurements of current versus time from an experimental system where the electrodissolution of copper in a phosphoric acid solution takes place. We investigate transitions from steady to oscillatory behavior and from period-one to period-two oscillations. Such procedures can be used in the analysis of systems for which no adequate phenomenological models exist.

KW - Bifurcations

KW - Electrochemical Oscillations

KW - Neural Networks

KW - Nonlinear Dynamics

KW - Signal Processing

UR - https://www.scopus.com/pages/publications/0025596515

UR - https://www.scopus.com/inward/citedby.url?scp=0025596515&partnerID=8YFLogxK

U2 - 10.1016/0009-2509(90)80079-T

DO - 10.1016/0009-2509(90)80079-T

M3 - Article

AN - SCOPUS:0025596515

SN - 0009-2509

VL - 45

SP - 2075

EP - 2081

JO - Chemical Engineering Science

JF - Chemical Engineering Science

IS - 8

ER -

Nonlinear signal processing and system identification: applications to time series from electrochemical reactions

Abstract

All Science Journal Classification (ASJC) codes

Keywords

Access to Document

Other files and links

Fingerprint

Cite this