A method is presented for investigating the periodic signal content of time series in which a number of signals is present, such as arising from the observation of multiperiodic oscillating stars in observational asteroseismology. Standard Fourier analysis tends only to be effective in cases when the data are perfectly regularly sampled. During normal telescope operation it is often the case that there are large, diurnal, gaps in the data, that data are missing, or that the data are not regularly sampled at all. For this reason it is advantageous to perform the analysis as much as possible in the time domain. Furthermore, for quantitative analyses of the frequency content and power of all real signals, it is of importance to have good estim...
We present a method for the Fourier analysis of gapped time series for application in asteroseismolo...
Several algorithms for the spectral analysis of irregularly sampled random processes can estimate th...
We review spectral analysis and its application in inference for stationary processes. As can be see...
Temporal gaps in discrete sampling sequences produce spurious Fourier components at the intermodulat...
We evaluate the quality of spectral restoration in the case of irregular sampled signals in astronom...
In this paper we present a new method for the Fourier spectral analysis of periodic signals, which t...
In this paper we present a new method fo,r the Fourier spectral analysis of periodic signals, which ...
Context.The location of pure frequencies in the spectrum of an irregularly sampled time series is an...
Asteroseismic time-series data have imprints of stellar oscillation modes, whose detection and chara...
In order to determine the Fourier transform of a quasi-periodic time series (linear problem), or the...
Two simple period determination schemes are discussed. They are well suited to problems involving no...
International audienceContext: The location of pure frequencies in the spectrum of an irregularly sa...
In this paper, we present a spectral analysis method based upon least square approximation. Our meth...
We develop a general framework for the frequency analysis of irregularly sampled time series. It is ...
Context. Solar-like oscillations exhibit a regular pattern of frequencies. This pattern is dominated...
We present a method for the Fourier analysis of gapped time series for application in asteroseismolo...
Several algorithms for the spectral analysis of irregularly sampled random processes can estimate th...
We review spectral analysis and its application in inference for stationary processes. As can be see...
Temporal gaps in discrete sampling sequences produce spurious Fourier components at the intermodulat...
We evaluate the quality of spectral restoration in the case of irregular sampled signals in astronom...
In this paper we present a new method for the Fourier spectral analysis of periodic signals, which t...
In this paper we present a new method fo,r the Fourier spectral analysis of periodic signals, which ...
Context.The location of pure frequencies in the spectrum of an irregularly sampled time series is an...
Asteroseismic time-series data have imprints of stellar oscillation modes, whose detection and chara...
In order to determine the Fourier transform of a quasi-periodic time series (linear problem), or the...
Two simple period determination schemes are discussed. They are well suited to problems involving no...
International audienceContext: The location of pure frequencies in the spectrum of an irregularly sa...
In this paper, we present a spectral analysis method based upon least square approximation. Our meth...
We develop a general framework for the frequency analysis of irregularly sampled time series. It is ...
Context. Solar-like oscillations exhibit a regular pattern of frequencies. This pattern is dominated...
We present a method for the Fourier analysis of gapped time series for application in asteroseismolo...
Several algorithms for the spectral analysis of irregularly sampled random processes can estimate th...
We review spectral analysis and its application in inference for stationary processes. As can be see...