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Model-based probability density function estimation

Model-based probability density function estimation,10.1109/97.735424,IEEE Signal Processing Letters,Steven Kay

Model-based probability density function estimation   (Citations: 12)
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Noting that the probability density function of a continuous random variable has similar properties to a power spectral density, a new class of probability density function estimators is described. The specific model examined is the autoregressive model, although the extension to other time series models is evident. An example is given to illustrate the approach
Journal: IEEE Signal Processing Letters - IEEE SIGNAL PROCESS LETT , vol. 5, no. 12, pp. 318-320, 1998
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    • ...Kay preciously proposed a model-based estimator [1] with better performance in that region, which, however, could only be employed for estimating the distribution with symmetric PDF...
    • ...Equation (2) is called sample moment estimator [1] or the sample CF [3] . Through (1) and (2), the PDF becomes...
    • ...In Gaussian-mixture distribution [1] simulation part, we also compared the proposed estimator with Kay’s model-based estimator...

    Junhao Xieet al. Probability Density Function Estimation Based on Windowed Fourier Tran...

    • ...Noting the close relationship between a pdf and a psd we can obtain an autocorrelation function whose Fourier transform is a scaled version of the desired pdf [5]...

    David Luengoet al. Underdetermined blind separation of sparse sources with instantaneous ...

    • ...AR-PDF estimation was also discussed in [13] and [14]...

    Jean-François Bercheret al. Estimating the entropy of a signal with applications

    • ...In this paper, we exploit the parallelism between the probability density function (PDF) of a random variable and the power spectral density (PSD) of a related random process [6, 7]. Once the problem is formulated in this way, any spectral estimation technique can be applied to estimate the mixing matrix...
    • ...(5) This is equation shows the way to estimate PDF’s using spectral estimation techniques [6, 7]: if we are able to determine the sequence φΩ[k], its PSD evaluated in the interval [−π, π] will be the PDF of Ω. Next we show how to find φΩ[k]...

    L. Vielvaet al. ESTIMATION OF THE MIXING MATRIX FOR UNDERDETERMINED BLIND SOURCE SEPAR...

    • ...For instance, in [8] the authors proposed to use nonparametric estimators of the PSD to estimate the PDF and in [4, 9] the PDF is modeled as an autoregressive (AR) process...
    • ...For instance, this analogy is exploited in [8,9] to estimate the PDF and in [4] to estimate the entropy of a RV based on parametric and nonparametric PSD estimators...

    David Ramet al. ENTROPY AND KULLBACK-LEIBLER DIVERGENCE ESTIMATION BASED

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