International audienceIn this paper, we compre the time fresuency deconvolution method with the wavelets method. We apply our results on several dynamical systems and show the capability of the wavelet's method to reconstruct the attractor of a chaotic time series? We de-noise different data sets in order to rebuilt their attractor using the wavelets method. Tha applications concern temperatures, wind fluctuations, electricity spot prices and exchange rates
Wavelet analysis is a powerful tool that is already in use throughout science and engineering. The v...
My thesis investigates wavelet theory and methods underlying recent applications to time series anal...
This chapter presents a set of tools, which allow gathering information about the frequency componen...
International audienceSatisfactory method of removing noise from experimental chaotic data is still ...
A new technique, wavelet network, is introduced to predict chaotic time series. By using this techni...
The aim of this report is to present the most recent ideas related to time-frequency methods and par...
This paper talk addresses a new signal processing method for detecting chaos in time series. This pr...
The detection of chaotic behaviors in commodities, stock markets and weather data is usually complic...
International audienceThe detection of chaotic behaviors in commodities, stock markets and weather d...
In the present study, we apply deterministic chaos theory to investigate nonlinear dynamics in month...
Thesis (Master)--Izmir Institute of Technology, Electronics and Communication Engineering, Izmir, 20...
Wavelets orthogonally decompose data into different frequency components, and the temporal and frequ...
In this paper, classical surrogate data methods for testing hypotheses concerning nonlinearity in ti...
URL des Documents de travail :http://ces.univ-paris1.fr/cesdp/CESFramDP2008.htmClassification JEL : ...
Wavelet analysis is a powerful tool that is already in use throughout science and engineering. The v...
Wavelet analysis is a powerful tool that is already in use throughout science and engineering. The v...
My thesis investigates wavelet theory and methods underlying recent applications to time series anal...
This chapter presents a set of tools, which allow gathering information about the frequency componen...
International audienceSatisfactory method of removing noise from experimental chaotic data is still ...
A new technique, wavelet network, is introduced to predict chaotic time series. By using this techni...
The aim of this report is to present the most recent ideas related to time-frequency methods and par...
This paper talk addresses a new signal processing method for detecting chaos in time series. This pr...
The detection of chaotic behaviors in commodities, stock markets and weather data is usually complic...
International audienceThe detection of chaotic behaviors in commodities, stock markets and weather d...
In the present study, we apply deterministic chaos theory to investigate nonlinear dynamics in month...
Thesis (Master)--Izmir Institute of Technology, Electronics and Communication Engineering, Izmir, 20...
Wavelets orthogonally decompose data into different frequency components, and the temporal and frequ...
In this paper, classical surrogate data methods for testing hypotheses concerning nonlinearity in ti...
URL des Documents de travail :http://ces.univ-paris1.fr/cesdp/CESFramDP2008.htmClassification JEL : ...
Wavelet analysis is a powerful tool that is already in use throughout science and engineering. The v...
Wavelet analysis is a powerful tool that is already in use throughout science and engineering. The v...
My thesis investigates wavelet theory and methods underlying recent applications to time series anal...
This chapter presents a set of tools, which allow gathering information about the frequency componen...