Counting Process Systems: Identification and Stochastic Realization
نویسندگان
چکیده
منابع مشابه
Maximum Likelihood Identification and Realization of Stochastic Systems
A new maximum likelihood (ML) realization/identification technique is presented. The method utilizes the recently introduced eigensystem realization algorithm (ERA) in combination with a stochastic adaptive filter/fixed-interval smoother. The resulting algorithm, called ML/ERA, is thus capable of estimating a minimal, internally balanced realization for a stochastic system whose process and/or ...
متن کاملSubspace Identification of Closed Loop Systems by Stochastic Realization
We develop a closed loop subspace identification method based on stochastic realization theory. Using the preliminary orthogonal decomposition of (Picci and Katayama, 1996b) we show that, under the assumption that the exogenous input is feedback-free and persistently exciting (PE), the identification of closed loop systems is divided into two subproblems: the deterministic identification of the...
متن کاملCausality and stochastic realization
The study of Granger causality has been mainly preoccupied with time series. We will instead concentrate on continuous time processes. Many systems to which it is natural to apply tests of causality take place in continuous time. For example, this is generally the case within economy. In the first part of this paper, we give a generalization of a causality relationship “G is a cause of E within...
متن کاملEfficient multiscale stochastic realization
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 secondorde...
متن کاملMultiscale Stochastic Realization
We develop a realization theory for a class of Inultiscale stochastic processes having whitenoise driven, scale-recursive dynamics that are indexed by the nodes of a tree. Given the correlation structure of a 1-D or 2-D random process, our methods provide a systematic way to realize the given correlation as the finest scale of a multiscale process. Motivated by Akaike's use of canonical correla...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Journal of the Operational Research Society
سال: 1992
ISSN: 0160-5682
DOI: 10.2307/2583582