Delay reconstruction for multiprobe signals

Mark Muldoon; David S. Broomhead; Jeremy P Huke

Delay reconstruction for multiprobe signals

Mark Muldoon, David S. Broomhead, Jeremy P Huke

Applied Mathematics

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

Abstract

A physical system governed by low-dimensional dynamics may be described completely with just a few measurements. Once one has such a description, any further measurements are redundant-one ought to be able to determine the results from what one already knows. Here we apply this idea to multivariate time series; we use the signal in one of the channels to build a model of the underlying system, then use the model to predict all the other channels. We demonstrate the method on a signal from a fluid-mechanical experiment, then discuss the implications for signal compression and for the secrecy of messages masked by chaotic noise.

Original language	English
Title of host publication	IEE Colloquium on Exploiting Chaos in Signal Processing
Publisher	Institution of Engineering and Technology
Pages	3/1-3/6
Number of pages	6
Publication status	Published - Jun 1994
Event	IEE Colloquium on Exploiting Chaos in Signal Processing - London, United Kingdom Duration: 6 Jun 1994 → 6 Jun 1994

Conference

Conference	IEE Colloquium on Exploiting Chaos in Signal Processing
Country/Territory	United Kingdom
City	London
Period	6/06/94 → 6/06/94

Keywords

chaos
delay effects
signal reconstruction
time series

Access to Document

https://ieeexplore.ieee.org/document/369883

Cite this

@inproceedings{fbfe0c68b1014a8b8384029ffedee515,

title = "Delay reconstruction for multiprobe signals",

abstract = "A physical system governed by low-dimensional dynamics may be described completely with just a few measurements. Once one has such a description, any further measurements are redundant-one ought to be able to determine the results from what one already knows. Here we apply this idea to multivariate time series; we use the signal in one of the channels to build a model of the underlying system, then use the model to predict all the other channels. We demonstrate the method on a signal from a fluid-mechanical experiment, then discuss the implications for signal compression and for the secrecy of messages masked by chaotic noise.",

keywords = "chaos, delay effects, signal reconstruction, time series",

author = "Mark Muldoon and Broomhead, \{David S.\} and Huke, \{Jeremy P\}",

year = "1994",

month = jun,

language = "English",

pages = "3/1--3/6",

booktitle = "IEE Colloquium on Exploiting Chaos in Signal Processing",

publisher = "Institution of Engineering and Technology ",

address = "United Kingdom",

note = "IEE Colloquium on Exploiting Chaos in Signal Processing ; Conference date: 06-06-1994 Through 06-06-1994",

}

TY - GEN

T1 - Delay reconstruction for multiprobe signals

AU - Muldoon, Mark

AU - Broomhead, David S.

AU - Huke, Jeremy P

PY - 1994/6

Y1 - 1994/6

N2 - A physical system governed by low-dimensional dynamics may be described completely with just a few measurements. Once one has such a description, any further measurements are redundant-one ought to be able to determine the results from what one already knows. Here we apply this idea to multivariate time series; we use the signal in one of the channels to build a model of the underlying system, then use the model to predict all the other channels. We demonstrate the method on a signal from a fluid-mechanical experiment, then discuss the implications for signal compression and for the secrecy of messages masked by chaotic noise.

AB - A physical system governed by low-dimensional dynamics may be described completely with just a few measurements. Once one has such a description, any further measurements are redundant-one ought to be able to determine the results from what one already knows. Here we apply this idea to multivariate time series; we use the signal in one of the channels to build a model of the underlying system, then use the model to predict all the other channels. We demonstrate the method on a signal from a fluid-mechanical experiment, then discuss the implications for signal compression and for the secrecy of messages masked by chaotic noise.

KW - chaos

KW - delay effects

KW - signal reconstruction

KW - time series

M3 - Conference contribution

SP - 3/1-3/6

BT - IEE Colloquium on Exploiting Chaos in Signal Processing

PB - Institution of Engineering and Technology

T2 - IEE Colloquium on Exploiting Chaos in Signal Processing

Y2 - 6 June 1994 through 6 June 1994

ER -

Delay reconstruction for multiprobe signals

Abstract

Conference

Keywords

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Cite this