In this paper we introduce a generic form of structural decomposition for the constraint satisfaction problem, which we call a guarded decomposition. We show that many existing decomposition methods can be characterized in terms of finding guarded decompositions satisfying certain specified additional conditions. Using the guarded decomposition framework we are also able to define a new form of...

Meaningful quantification of data and structural uncertainties in conceptual rainfall-runoff modeling is a major scientific and engineering challenge. This paper focuses on the total predictive uncertainty and its decomposition into input and structural components under different inference scenarios. Several Bayesian inference schemes are investigated, differing in the treatment of rainfall and...

Abstract. We propose a method for the decomposition of modal formulae on processes with nondeterminism and probability with respect to Structural Operational Semantics. The purpose is to reduce the satisfaction problem of a formula for a process to verifying whether its subprocesses satisfy certain formulae obtained from the decomposition. To deal with the probabilistic behavior of processes, a...

In this paper, we present a structural decomposition for general single-input and single-output linear singular systems. Such a decomposition has a distinct feature of capturing and displaying all the structural properties, such as the .nite and in.nite zero structures and redundant dynamics, of the given system. It is expected to be a powerful tool in solving control problems for singular syst...

A method for the automatic detection of seizure in newborns is presented. The proposed method is derived from the ability to detect changes in signal structure as the newborn EEG changes from the background state to the seizure state. Matching Pursuit decomposition technique, with an overcomplete time−frequency dictionary, is shown to be an adequate technique for detecting changes in signal str...

Many scientific computing algorithms (in various domains, such as weather prediction, structural analysis, or electrical network analysis) strongly rely on solving fundamental matrix computation problems (such as linear system solving, eigenvalue decomposition, singular value decomposition, matrix nearness problems, joint diagonalization of matrices...). These problems are often solved using it...

This paper is a review which presents and explains the decomposition by clique minimal separators, which is a promising tool for representing and decomposing experimental data. The pace is leisurely, we give many examples and figures. Easy algorithms are provided to implement this decomposition. The historical and theoretical background is given, as well as sketches of proofs of the structural ...

A recent development in energy and environment decomposition analysis is the application of the technique to cross-country region comparisons. Cross-country region decomposition gives rise to several problems that do not normally occur in chronological decomposition of changes in a specific country. These include large variations in explanatory factors in the data, the measure of economic outpu...

Structural product form and decomposition results for stochastic Petri nets are surveyed, unified and extended. The contribution is threefold. First, the literature on structural results for product form over the number of tokens at the places is surveyed and rephrased completely in terms of T -invariants. Second, based on the underlying concept of group-local-balance, the product form results ...

Qualitative reasoning has been widely applied in the analysis of complex networks, but the loss of quantitative information easily result in reasoning conflict. In this article, we adopt a hierarchical decomposition strategy of the network, and present a general framework of qualitative graphical inference based on enhanced multi-level knowledge fusion so as to avoid reasoning conflict. The fra...