Consider a first order, linear and time-invariant discrete time system driven by Gaussian and zero mean white process noise, a pre-processor that accepts causal measurements of the state of the system, and a state estimator. The pre-processor and the state estimator are not co-located, and, at every timestep, the pre-processor sends either a real number or an erasure symbol to the estimator. We...

The Kitanidis filter is a natural extension of the Kalman to systems subject arbitrary unknown inputs or disturbances. Though optimality was founded for general time varying more than 30 years ago, its boundedness and stability analysis still limited time-invariant systems, up authors’ knowledge. In framework this article establishes upper lower bounds error covariance filter, as well all auxil...

inverse sampling design is generally considered to be appropriate technique when the population is divided into two subpopulations, one of which contains only few units. in this paper, we derive the horvitz-thompson estimator for the population mean under inverse sampling designs, where subpopulation sizes are known. we then introduce an alternative unbiased estimator, corresponding to post-str...

In this paper we propose a novel distributed state estimator for large-scale linear systems composed by subsystems interacting through state variables. The distributed state estimator has the following features: (i) local state estimators, each dedicated to the reconstruction of the states of a subsystem, are connected through a communication network with the parent-child topology induced by su...

A lexical transducer, first discussed in Karttunen, Kaplan and Zaenen 1992, is a specialised finite-state automaton that maps inflected surface forms to lexical forms, and vice versa. The lexical form consists of a canonical representation of the word and a sequence of tags that show the morphological characteristics of the form in question and its syntactic category. For example, a lexical tra...