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Listar por palabra clave "Gaussian noise (electronic)"

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Listar por palabra clave "Gaussian noise (electronic)"

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    An Approach to Handling Non-Gaussianity of Parameters and State Variables in Ensemble Kalman Filtering 
    Zhou ., Haiyan; Gómez-Hernández, J. Jaime; Hendricks Franssen, Hendrikus Johannes W; Li, Liangping (ELSEVIER SCI LTD, 2011)
    [EN] The ensemble Kalman filter (EnKF) is a commonly used real-time data assimilation algorithm in various disciplines. Here, the EnKF is applied, in a hydrogeological context, to condition log-conductivity realizations ...
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    Generalized matched subspace filter for dependent noise based on ICA 
    Moragues Escrivá, Jorge; Vergara Domínguez, Luís; Gosálbez Castillo, Jorge (Institute of Electrical and Electronics Engineers (IEEE), 2011-07)
    We propose a generalization of the matched subspace filter for the detection of unknown signals in a background of non-Gaussian and nonindependent noise. The generalization is based on a modification of the Rao test by ...
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    Hardware architecture of a gaussian noise generator based on inversion method 
    Gutiérrez, Roberto G.; Torres Carot, Vicente; Valls Coquillat, Javier (Institute of Electrical and Electronics Engineers (IEEE), 2012-08)
    In this brief, we present a hardware-based Gaussian noise generator (GNG) with low hardware cost, high generation rate, and high Gaussian tail accuracy. The proposed generator is based on a piecewise polynomial approximation ...
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    Improving detection of acoustic signals by means of a time and frequency multiple energy detectors 
    Moragues Escrivá, Jorge; Serrano Cartagena, Arturo; Vergara Domínguez, Luís; Gosálbez Castillo, Jorge (Institute of Electrical and Electronics Engineers (IEEE), 2011-08)
    Standard energy detectors (ED) are optimum to detect unknown signals in presence of uncorrelated Gaussian noise. However, in real applications the signal duration and bandwidth are unpredictable and this fact can considerably ...