Meryem Jabloun

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In previous published works [8, 3], we have studied the estimation of nonstationary monocomponent signals on short time-windows. Both of the instantaneous amplitude and frequency (IA/ IF) were modeled by polynomial functions. The maximization of the likelihood function was achieved by using a stochastic optimization technique: the Simulated An-nealing (SA).(More)
We consider the modeling of non-stationary discrete signals whose amplitude and frequency are assumed to be nonlinearly modulated over very short-time duration. We investigate the case where both instantaneous amplitude and frequency can be approximated by orthonormal polynomials. Previous works dealing with polynomial approximations refer to orthonormal(More)
The inverse problem of estimating the Particle Size Distribution (PSD) from Multiangle Dynamic Light Scattering measurements (MDLS) is considered using a Bayesian inference approach. We propose to model the multimodal PSD as a normal mixture with an unknown number of components (modes or peaks). In order to achieve the estimation of these variable dimension(More)