Abstract We propose an adaptive moment-matching framework for model order reduction of quadratic-bilinear systems. In this framework, important issue is the selection those shift frequencies where to be achieved. So far, choice often has been random or linked linear part nonlinear system. paper, we extend use existing a posteriori error bound general time invariant systems and develop greedy-ty...

Toward the development of an object recognition and positioning system, able to deal with arbitrary shaped objects in cluttered environments, we introduce methods for checking the match of two arbitrary curves in 2D or surfaces in 3D, when each of these subobjects (i.e., regions) is in arbitrary position, and we also show how to efficiently compute explicit expressions for the coordinate transf...

Many problems of operations research or decision science involve continuous probability distributions, whose handling may be sometimes unmanageable; in order to tackle this issue, different forms approximation methods can used. When constructing a k-point discrete random variable, moment matching, i.e., matching as many moments possible the original distribution, is most popular technique. This...

In the stochastic formulation of chemical reactions, the time evolution of the first M order statistical moments for the number of molecules of the different species involved is generally not closed, in the sense that they depend on moments of order higher than M. For analysis purposes, the time evolution of the first M order moments is often made to be closed by approximating the higher order ...

ontology is the main infrastructure of the semantic web which provides facilities for integration, searching and sharing of information on the web. development of ontologies as the basis of semantic web and their heterogeneities have led to the existence of ontology matching. by emerging large-scale ontologies in real domain, the ontology matching systems faced with some problem like memory con...

An efficient model-order reduction technique for general RLC networks is proposed. The method is extended from the previous projection-base moment matching method with considering both the circuit network and its corresponding adjoint network. By exploring symmetric properties of the MNA formulation, the proposed method needs only one half of the system moment information compared with the prev...

Shape feature extraction is a key research direction on wheat leaf disease recognition. In order to resolve the problem of translation, scaling and rotation transformation invariance on shape matching, the invariant moment theory was introduced to shape feature extraction and seven Hu invariant moment parameters were defined as shape features. Meanwhile the present algorithm was used and new pa...

We propose a fast and scalable method for semi-supervised learning of sequence models, based on anchor words and moment matching. Our method can handle hidden Markov models with feature-based log-linear emissions. Unlike other semi-supervised methods, no decoding passes are necessary on the unlabeled data and no graph needs to be constructed— only one pass is necessary to collect moment statist...

The density estimates considered in this paper comprise a base density and an adjustment component consisting of a linear combination of orthogonal polynomials. It is shown that, in the context of density approximation, the coefficients of the linear combination can be determined either from a moment-matching technique or a weighted least-squares approach. A kernel representation of the corresp...