Efficient multiscale stochastic realization
نویسندگان
چکیده
Few fast statistical signal processing algorithms exist for large problems involving non-stationary processes and irregular measurements. A recently introduced class of multiscale autoregressive models indexed by trees admits signal processing algorithms which can efficiently deal with problems of this type. In this paper we provide a novel and efficient algorithm for translating any secondorder prior model to a multiscale autoregressive prior model so that these efficient signal processing algorithms may be applied.
منابع مشابه
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