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Titlebook: Analysis and Optimization of Systems; Proceedings of the S A. Bensoussan,J. L. Lions Conference proceedings 1984 Springer-Verlag Berlin Hei

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楼主: Bush
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,Description d’un detecteur sequentiel de changements brusques de dynamiques des modeles arma,sequentially performed by an Extended Kalman Filter which provides both the parameters of the model and a "pseudo-innovation" sequence..That independant sequence is multiply by itself with a link of one step to define a decision variable and to detect a change of level.
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Bayesian estimation of a spectrum of a nonstationary autoregressive process,wo most frequently used models of process parameters‘ variation : the Kalman filter model and the fadding memory (exponential forgetting) one. The efficient computational algorithms are indicated and the results of computer simulation are presented.
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A general class of estimators for the wigner-ville spectrum of non-stationary processes,requency representation of a process is based on the covariance function and, for quasi-stationary processes, estimators can be defined by means of local time-averaging. We propose here a general class of such estimators relying on an arbitrary weighting function and discuss their first and second o
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Bayesian estimation of a spectrum of a nonstationary autoregressive process,d by minimization of the Bayesian risk function corresponding to the normalized mean square spectral error measure. The obtained results concern the two most frequently used models of process parameters‘ variation : the Kalman filter model and the fadding memory (exponential forgetting) one. The eff
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