Differential Representation and Markov Property of Generalized Random Fields

نویسندگان

  • V. V. Anh
  • M. D. Ruiz-Medina
  • J. M. Angulo
چکیده

Using the geometric properties of Sobolev spaces of integer order and a duality condition, the covariance operators of a generalized random field and its dual can be factorized. Via this covariance factorization, a representation of the generalized random field is obtained as a stochastic equation driven by generalized white noise. This stochastic equation becomes a differential equation under the orthogonality of the dual random field. The solution to this equation satisfies the weak-sense Markov property of integer order. Furthermore, such a solution admits a mean-square series expansion in terms of the eigenfunctions associated with the pure point spectrum of the corresponding covariance operator. From this representation, the relationship between the covariance function and Partially supported by the Australian Research Council grant A 896

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Fractional Generalized Random Fields on Bounded Domains

Using the theory of generalized random fields on fractional Sobolev spaces on bounded domains, and the concept of dual generalized random field, this paper introduces a class of random fields with fractional-order pure point spectra. The covariance factorization of an a-generalized random field having a dual is established, leading to a white-noise linearfilter representation, which reduces to ...

متن کامل

Isotropic Gauss - Markov Currents *

A natural definition of the Markov property for multi-parameter random processes (random fields) is the following. Let {Xt, tEIR N} be a multiparameter process. For any set D in N. N, let a D denote the a-field generated by {Xt, tED}. The field {Xt, tEN. u} is said to be Markov (or Markov of degree 1 [6], or sharp Markov) if, for any bounded open set D with smooth boundary, oD and ape are condi...

متن کامل

An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach

Continuously indexed Gaussian fields (GFs) are the most important ingredient in spatial statistical modelling and geostatistics. The specification through the covariance function gives an intuitive interpretation of the field properties. On the computational side, GFs are hampered with the big n problem, since the cost of factorizing dense matrices is cubic in the dimension. Although computatio...

متن کامل

Telescoping Recursive Representations and Estimation of Gauss-Markov Random Fields

We present telescoping recursive representations for both continuous and discrete indexed noncausal Gauss-Markov random fields. Our recursions start at the boundary (for example, a hypersurface in R, d ≥ 1) and telescope inwards. Under appropriate conditions, the recursions for the random field are differential/difference representations driven by white noise, for which we can use standard recu...

متن کامل

Gauss-Markov random fields (CMrf) with continuous indices

Gauss–Markov random fields (GMrf’s) play an important role in the modeling of physical phenomena. The paper addresses the second-order characterization and the sample path description of GMrf’s when the indexing parameters take values in bounded subsets of <; d 1. Using results of Pitt, we give conditions for the covariance of a GMrf to be the Green’s function of a partial differential operator...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2001