We present image compression method based on block palletizing. Image block is partitioned into four subsets, and each subset is palletized by 2 or 4 colors from the quasioptimal local palette, constructed for the who...
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ISBN:
(纸本)9781581131987
We present image compression method based on block palletizing. Image block is partitioned into four subsets, and each subset is palletized by 2 or 4 colors from the quasioptimal local palette, constructed for the whole block. Index map for the whole block, being the union of index maps for subsets, is thus only 1 or 2 bits deep, while the local palette may consist of 8 or even 16 colors. The local palette has a specific geometrical configuration in RGB color space, determined by only 2 colors. These two colors are stored explicitly, and the rest are reconstructed at the decompression stage. Compressed block consists, essentially, of the index map, palette description and partition description. This format allows fast access to randomly chosen pixels, and high reconstruction quality for compression ratios from 8 to 12, which is useful for texture storage in 3D graphics applications where real-time decompression is crucial.
Biological data mining aims to extract significant information from DNA, RNA and proteins. The significant information may refer to motifs, functional sites, clustering and classification rules. This paper presents an...
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ISBN:
(纸本)1581132336
Biological data mining aims to extract significant information from DNA, RNA and proteins. The significant information may refer to motifs, functional sites, clustering and classification rules. This paper presents an example of biological data mining: The classification of protein sequences using neural networks. We propose new techniques to extract features from protein data and use them in combination with the Bayesian neural network to classify protein sequences obtained from the PIR protein database maintained at the National Biomedical Research Foundation. To evaluate the performance of the proposed approach, we compare it with other protein classifiers built based on sequence alignment and machine learning methods. Experimental results show the high precision of the proposed classifier and the complementarity of the tools studied in the paper.
In this paper we study a multidimensional continued fraction algorithm which is related to the Modified Jacobi-Perron algorithm considered by Podsypanin and Schweiger. We demonstrate that this algorithm has many impor...
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In this paper we study a multidimensional continued fraction algorithm which is related to the Modified Jacobi-Perron algorithm considered by Podsypanin and Schweiger. We demonstrate that this algorithm has many important properties which are natural generalisations of properties of one-dimensional continued fractions. For this reason, we call the transformation associated to the algorithm the d-dimensional Gauss transformation. We construct a coordinate system for the natural extension which reveals its symmetries and allows one to give an explicit formula for the density of its invariant measure. We also discuss the ergodic properties of this invariant measure.
We derive an exact expression for the two-point correlation function for quantum star graphs in the limit as the number of bonds tends to infinity. This turns out to be identical to the corresponding result for certai...
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We derive an exact expression for the two-point correlation function for quantum star graphs in the limit as the number of bonds tends to infinity. This turns out to be identical to the corresponding result for certain Šeba billiards in the semiclassical limit. Reasons for this are discussed. The formula we derive is also shown to be equivalent to a series expansion for the form factor - the Fourier transform of the two-point correlation function - previously calculated using periodic orbit theory.
The tasks of monitoring the information related to the work of multi-agent systems are considered, allowing discovery of the regularities of structural organization of agent sets and sets of problems solved by them. A...
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The paper studies the problem of pricing contingent claims in the situation where the constraints imposed on an investor's portfolios are important. There are two types of rule of constraint: under a rigid rule, a...
The paper studies the problem of pricing contingent claims in the situation where the constraints imposed on an investor's portfolios are important. There are two types of rule of constraint: under a rigid rule, an investor must strictly limit his portfolios inside the constraint;under an elastic rule, an investor pays a penalty when the constraint is violated. The central problem of pricing a contingent claim is to determine the initial investment required to duplicate the contingent claim. The following results are obtained: (i) under elastic rules, the cost to duplicate a contingent claim exists and is unique;(ii) this cost depends nonlinearly and convexly on the contingent claim;(iii) the cost under rigid rules resulting from passing the penalty to infinity is also a nonlinear and convex function of the contingent claim. Owing to this nonlinearity, the cost of duplication may be or may not be the nonarbitrage price of the contingent claim;this depends on how the market organizes the production of contingent claims. The conclusion that the cost of duplication is a convex function of the contingent claim provides an explanation for why the service of providing contingent claims is often a highly profitable business. The main math.matical tool in the analysis is backward stochastic differential equations (BSDEs). In fact the cost to duplicate a contingent claim is the solution of a BSDE in which the contingent claim is the terminal value.
The paper presents a new approach for shape recovery based on integrating geometric and photometric information. We consider 3D objects which are symmetric with respect to a plane (e.g., faces) and their reconstructio...
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Practical applications of chaos are likely to face problems of reliability because of the existence of multiple attractors and periodic windows in most chaotic dynamical systems. In this paper we show that robust chao...
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Practical applications of chaos are likely to face problems of reliability because of the existence of multiple attractors and periodic windows in most chaotic dynamical systems. In this paper we show that robust chaos, defined by the absence of periodic windows and coexisting attractors in some neighborhood of the parameter space, can occur in piecewise smooth systems and obtain the conditions of its occurrence. We demonstrate experimental evidence of this phenomenon in power electronic circuits.
A Multiple Structural Alignment algorithm is presented. The algorithm accepts an ensemble of protein structures and finds the largest substructure (core) of Cα atoms whose geometric configuration appear in all the mo...
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The thermal processes proceeding within a perfused tissue in the presence of a vessel are considered. The Pennes bio-heat transfer equation determines the steady state temperature field in tissue sub-domain, while the...
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The thermal processes proceeding within a perfused tissue in the presence of a vessel are considered. The Pennes bio-heat transfer equation determines the steady state temperature field in tissue sub-domain, while the ordinary differential equation resulting from the energy balance describes the change of blood temperature along the vessel. The coupling of above equations results from the boundary condition given on the blood vessel wall. The problem is solved using the combined numerical algorithm, in particular the boundary element method (for the tissue sub-domain) and the finite differences method (for blood vessel sub-domain).
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