Red spectra from white and blue noise
The value of maps of the interval in modelling population dynamics has recently been called into question because temporal variations from such maps have blue or white power spectra, whereas many observations of real populations show time-series with red spectra. One way to deal with this discrepanc...
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Veröffentlicht in: | Proceedings of the Royal Society. B, Biological sciences Biological sciences, 1999-02, Vol.266 (1416), p.311-314 |
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container_title | Proceedings of the Royal Society. B, Biological sciences |
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creator | Balmforth, Neil J. Provenzale, Antonello Spiegel, Edward A. Martens, M. Tresser, Charles Chai, Wa Wu |
description | The value of maps of the interval in modelling population dynamics has recently been called into question because temporal variations from such maps have blue or white power spectra, whereas many observations of real populations show time-series with red spectra. One way to deal with this discrepancy is to introduce chaotic or stochastic fluctuations in the parameters of the map. This leads to on-off intermittency and can markedly redden the spectrum produced by a model that does not by itself have a red spectrum. The parameter fluctuations need not themselves have a red spectrum in order to achieve this effect. Because the power spectrum is not invariant under a change of variable, another way to redden the spectrum is by a suitable transformation of the variables used. The question this poses is whether spectra are the best means of characterizing a fluctuating variable. |
doi_str_mv | 10.1098/rspb.1999.0639 |
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One way to deal with this discrepancy is to introduce chaotic or stochastic fluctuations in the parameters of the map. This leads to on-off intermittency and can markedly redden the spectrum produced by a model that does not by itself have a red spectrum. The parameter fluctuations need not themselves have a red spectrum in order to achieve this effect. Because the power spectrum is not invariant under a change of variable, another way to redden the spectrum is by a suitable transformation of the variables used. 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One way to deal with this discrepancy is to introduce chaotic or stochastic fluctuations in the parameters of the map. This leads to on-off intermittency and can markedly redden the spectrum produced by a model that does not by itself have a red spectrum. The parameter fluctuations need not themselves have a red spectrum in order to achieve this effect. Because the power spectrum is not invariant under a change of variable, another way to redden the spectrum is by a suitable transformation of the variables used. The question this poses is whether spectra are the best means of characterizing a fluctuating variable.</abstract><pub>The Royal Society</pub><doi>10.1098/rspb.1999.0639</doi><tpages>4</tpages><oa>free_for_read</oa></addata></record> |
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source | Jstor Complete Legacy; PubMed Central |
subjects | 1/f Spectra Acoustic spectra Dynamic modeling Dynamical Systems Economic fluctuations Environmental Effects Logistics Low frequencies Noise spectra On-Off Intermittency Population Dynamics Time series Time series models White noise |
title | Red spectra from white and blue noise |
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