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Consider a $d\times d$ matrix $M$ whose rows are independent centered non-degenerate Gaussian vectors $\xi_1,...,\xi_d$ with covariance matrices $\Sigma_1,...,\Sigma_d$. Denote by $\mathcal{E}_i$ the ...
The structure of Gaussian random fields over high levels is a well researched and well understood area, particularly if the field is smooth. However, the question as to whether or not two or more poin...
Abstract: For a random field on a general discrete set, we introduce a condition that the range of the correlation from each site is within a predefined compact set D. For such a random field {\omega}...
Abstract: For a given pair of positive integers $d$ and $N$ with $N \geq 2$, for strictly stationary random fields that are indexed by the $d$-dimensional integer lattice and satisfy $N$-tuplewise ind...
Extrapolation of stable random fields     Extrapolation  random field  stable distribution       font style='font-size:12px;'> 2011/8/30
Abstract: In this paper, we discuss three extrapolation methods for alpha-stable random fields with 1<alpha<=2. We justify them, giving proofs of the existence and uniqueness of the solutions for each...
The task of crop type classification with multitemporal imagery is nowadays often done applying classifiers that are originally developed for single images like support vector machines (SVM). These...
In this paper we study the asymptotic normality of the normalized partial sum of a Hilbert-space valued strictly stationary random field satisfying the interlaced ρ′-mixing condition.
We consider Markov random fields of discrete spins on the lattice Zd. We use a technique of coupling of conditional distributions. If under the coupling the disagreement cluster is “sufficiently” subc...
Let $X=\{X(t),t\in\mathbb{R}^N\}$ be a random field with values in $\mathbb{R}^d$. For any finite Borel measure $\mu$ and analytic set $E\subset\mathbb{R}^N$, the Hausdorff and packing dimensions of t...
Pair-wise Markov random fields (MRF) are considered for application to the development of low complexity, iterative MIMO detection. Specifically, we consider two types of MRF, namely, the fully-conne...
For a class of Z2 Markov Random Fields (MRFs) μ, we show that the sequence of successive differences of entropies of induced MRFs on strips of height n converges exponentially fast (in n) to the entro...
In this paper, the convergence of negatively associated random fields is investigated, two sufficiency conditions for the law of the logarithum are obtained by the Rosenthal and maximal Rosenthal ineq...
A statistical model of protein families, called profile conditional random fields (CRFs), is proposed. This model may be regarded as an integration of the profile hidden Markov model (HMM) and the Fin...
The Complexity of Distinguishing Markov Random Fields     The Complexity  Markov  Random Fields       font style='font-size:12px;'> 2012/12/3
Markov random fields are often used to model high dimensional distributions in a number of applied areas. A number of recent papers have studied the problem of reconstructing a dependency graph of bou...

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