Adaptive Local Iterative Filtering: A Promising Technique for the Analysis of Nonstationary Signals
| Autor: | Rodolfo Gerardo Ezquer, Luca Spogli, Massimo Materassi, Antonio Cicone, Haomin Zhou, Mirko Piersanti |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
010504 meteorology & atmospheric sciences
Computer science 02 engineering and technology 01 natural sciences Ciencias de la Tierra y relacionadas con el Medio Ambiente ionospheric scintillation Interplanetary scintillation NONSTATIONARY AND NONLINEARITY multiscale statistics 0202 electrical engineering electronic engineering information engineering Statistical analysis Time series 0105 earth and related environmental sciences nonlinear geophysics NEW DATA ANALISYS TOOL RADIO SCINTILLATION SIGNAL STATISTICAL ANALYSIS 020206 networking & telecommunications time series analysis Geophysics Space and Planetary Science Iterative filtering Meteorología y Ciencias Atmosféricas Algorithm CIENCIAS NATURALES Y EXACTAS |
| Zdroj: | Journal of geophysical research. Space physics 123 (2018): 1031–1046. doi:10.1002/2017JA024153 info:cnr-pdr/source/autori:Piersanti M.; Materassi M.; Cicone A.; Spogli L.; Zhou H.; Ezquer R.G./titolo:Adaptive Local Iterative Filtering: A Promising Technique for the Analysis of Nonstationary Signals/doi:10.1002%2F2017JA024153/rivista:Journal of geophysical research. Space physics (Print)/anno:2018/pagina_da:1031/pagina_a:1046/intervallo_pagine:1031–1046/volume:123 |
| DOI: | 10.1002/2017JA024153 |
| Popis: | Many real-life signals and, in particular, in the space physics domain, exhibit variations acrossdifferent temporal scales. Hence, their statistical momenta may depend on the time scale at which the signal is studied. To identify and quantify such variations, a time-frequency analysis has to be performed on these signals. The dependence of the statistical properties of a signal fluctuation on the space and time scales is the distinctive character of systems with nonlinear couplings among different modes. Hence, assessing how the statistics of signal fluctuations vary with scale will be of help in understanding the corresponding multiscale statistics of such dynamics. This paper presents a new multiscale data analysis technique, the adaptive local iterative filtering (ALIF), which allows to describe the multiscale nature of the geophysical signal studied better than via Fourier transform, and improves scale resolution with respect to discrete wavelet transform. The example of geophysical signal, to which ALIF has been applied, is ionospheric radio power scintillation on L band. ALIF appears to be a promising technique to study the small-scale structures of radio scintillation due to ionospheric turbulence. Fil: Piersanti, M.. University Of L Aquila, L Aquila, Italy; Italia Fil: Materassi, M.. National Research Council, Rome, Italy; Italia Fil: Cicone, A.. Universitá Degli Studi Dell Aquila, L Aquila, Italy; Italia Fil: Spogli, L.. Istituto Nazionale Di Geofisica E Vulcanologia; Italia Fil: Zhou, H.. Georgia Institute Of Technology, Atlanta, Ga, Usa; Estados Unidos Fil: Ezquer, Rodolfo Gerardo. Universidad Tecnológica Nacional; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Física. Laboratorio de Ionosfera; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; Argentina |
| Databáze: | OpenAIRE |
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