Astronomical component estimation (ACE v.1) by time-variant sinusoidal modeling
Guardat en:
| Publicat a: | Geoscientific Model Development vol. 9, no. 10 (2016), p. 3517 |
|---|---|
| Autor principal: | |
| Altres autors: | , , , |
| Publicat: |
Copernicus GmbH
|
| Matèries: | |
| Accés en línia: | Citation/Abstract Full Text Full Text - PDF |
| Etiquetes: |
Sense etiquetes, Sigues el primer a etiquetar aquest registre!
|
MARC
| LEADER | 00000nab a2200000uu 4500 | ||
|---|---|---|---|
| 001 | 2414209494 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 1991-962X | ||
| 022 | |a 1991-9603 | ||
| 024 | 7 | |a 10.5194/gmd-9-3517-2016 |2 doi | |
| 035 | |a 2414209494 | ||
| 045 | 2 | |b d20161001 |b d20161031 | |
| 084 | |a 123629 |2 nlm | ||
| 100 | 1 | |a Sinnesael, Matthias |u Analytical, Environmental, & Geo-Chemistry, Vrije Universiteit Brussel, 1050 Brussels, Belgium | |
| 245 | 1 | |a Astronomical component estimation (ACE v.1) by time-variant sinusoidal modeling | |
| 260 | |b Copernicus GmbH |c 2016 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Accurately deciphering periodic variations in paleoclimate proxy signals is essential for cyclostratigraphy. Classical spectral analysis often relies on methods based on (fast) Fourier transformation. This technique has no unique solution separating variations in amplitude and frequency. This characteristic can make it difficult to correctly interpret a proxy's power spectrum or to accurately evaluate simultaneous changes in amplitude and frequency in evolutionary analyses. This drawback is circumvented by using a polynomial approach to estimate instantaneous amplitude and frequency in orbital components. This approach was proven useful to characterize audio signals (music and speech), which are non-stationary in nature. Paleoclimate proxy signals and audio signals share similar dynamics; the only difference is the frequency relationship between the different components. A harmonic-frequency relationship exists in audio signals, whereas this relation is non-harmonic in paleoclimate signals. However, this difference is irrelevant for the problem of separating simultaneous changes in amplitude and frequency.Using an approach with overlapping analysis frames, the model (Astronomical Component Estimation, version 1: ACE v.1) captures time variations of an orbital component by modulating a stationary sinusoid centered at its mean frequency, with a single polynomial. Hence, the parameters that determine the model are the mean frequency of the orbital component and the polynomial coefficients. The first parameter depends on geologic interpretations, whereas the latter are estimated by means of linear least-squares. As output, the model provides the orbital component waveform, either in the depth or time domain. Uncertainty analyses of the model estimates are performed using Monte Carlo simulations. Furthermore, it allows for a unique decomposition of the signal into its instantaneous amplitude and frequency. Frequency modulation patterns reconstruct changes in accumulation rate, whereas amplitude modulation identifies eccentricity-modulated precession. The functioning of the time-variant sinusoidal model is illustrated and validated using a synthetic insolation signal. The new modeling approach is tested on two case studies: (1) a Pliocene–Pleistocene benthic <inline-formula>δ18</inline-formula>O record from Ocean Drilling Program (ODP) Site 846 and (2) a Danian magnetic susceptibility record from the Contessa Highway section, Gubbio, Italy. | |
| 653 | |a Music | ||
| 653 | |a Wavelet transforms | ||
| 653 | |a Fast Fourier transformations | ||
| 653 | |a Signal processing | ||
| 653 | |a Polynomials | ||
| 653 | |a Astronomical models | ||
| 653 | |a Time domain analysis | ||
| 653 | |a Spectral analysis | ||
| 653 | |a Noise | ||
| 653 | |a Uncertainty analysis | ||
| 653 | |a Periodic variations | ||
| 653 | |a Climate change | ||
| 653 | |a Drilling | ||
| 653 | |a Computer simulation | ||
| 653 | |a Magnetic susceptibility | ||
| 653 | |a Amplitude modulation | ||
| 653 | |a Amplitude | ||
| 653 | |a Pliocene | ||
| 653 | |a Benthos | ||
| 653 | |a Variation | ||
| 653 | |a Frequency analysis | ||
| 653 | |a Pleistocene | ||
| 653 | |a Audio signals | ||
| 653 | |a Parameter estimation | ||
| 653 | |a Waveforms | ||
| 653 | |a Spectrum analysis | ||
| 653 | |a Frequency dependence | ||
| 653 | |a Case studies | ||
| 653 | |a Modelling | ||
| 653 | |a Magnetic permeability | ||
| 653 | |a Ocean Drilling Program (ODP) | ||
| 653 | |a Coefficients | ||
| 653 | |a Paleoclimate | ||
| 653 | |a Components | ||
| 653 | |a Archives & records | ||
| 653 | |a Frequency modulation | ||
| 653 | |a Sedimentation & deposition | ||
| 653 | |a Parameters | ||
| 653 | |a Statistical methods | ||
| 653 | |a Fourier analysis | ||
| 653 | |a Monte Carlo simulation | ||
| 653 | |a Environmental | ||
| 700 | 1 | |a Zivanovic, Miroslav |u Department of Electrical and Electronic Engineering, Universidad Pública de Navarra, 31006 Pamplona, Spain | |
| 700 | 1 | |a De Vleeschouwer, David |u Analytical, Environmental, & Geo-Chemistry, Vrije Universiteit Brussel, 1050 Brussels, Belgium; MARUM, Center for Marine Environmental Science, Leobener Strasse, 28359 Bremen, Germany | |
| 700 | 1 | |a Claeys, Philippe |u Analytical, Environmental, & Geo-Chemistry, Vrije Universiteit Brussel, 1050 Brussels, Belgium | |
| 700 | 1 | |a Schoukens, Johan |u Department of Fundamental Electricity and Instrumentation, Vrije Universiteit Brussel, 1050 Brussels, Belgium | |
| 773 | 0 | |t Geoscientific Model Development |g vol. 9, no. 10 (2016), p. 3517 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/2414209494/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/2414209494/fulltext/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/2414209494/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |