11 resultados para Spectrally bounded

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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This article provides importance sampling algorithms for computing the probabilities of various types ruin of spectrally negative Lévy risk processes, which are ruin over the infinite time horizon, ruin within a finite time horizon and ruin past a finite time horizon. For the special case of the compound Poisson process perturbed by diffusion, algorithms for computing probabilities of ruins by creeping (i.e. induced by the diffusion term) and by jumping (i.e. by a claim amount) are provided. It is shown that these algorithms have either bounded relative error or logarithmic efficiency, as t,x→∞t,x→∞, where t>0t>0 is the time horizon and x>0x>0 is the starting point of the risk process, with y=t/xy=t/x held constant and assumed either below or above a certain constant.

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OBJECT: Fat suppressed 3D steady-state free precession (SSFP) sequences are of special interest in cartilage imaging due to their short repetition time in combination with high signal-to-noise ratio. At low-to-high fields (1.5-3.0 T), spectral spatial (spsp) radio frequency (RF) pulses perform superiorly over conventional saturation of the fat signal (FATSAT pulses). However, ultra-high fields (7.0 T and more) may offer alternative fat suppression techniques as a result of the increased chemical shift. MATERIALS AND METHODS: Application of a single, frequency selective, RF pulse is compared to spsp excitation for water (or fat) selective imaging at 7.0 T. RESULTS: For SSFP, application of a single frequency selective RF pulse for selective water or fat excitation performs beneficially over the commonly applied spsp RF pulses. In addition to the overall improved fat suppression, the application of single RF pulses leads to decreased power depositions, still representing one of the major restrictions in the design and application of many pulse sequences at ultra-high fields. CONCLUSION: The ease of applicability and implementation of single frequency selective RF pulses at ultra-high-fields might be of great benefit for a vast number of applications where fat suppression is desirable or fat-water separation is needed for quantification purposes.

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We conducted a stratigraphic analysis of the South Polar Layered Deposits (SPLDs) in Promethei Lingula (PL, Mars) based on the identification of regional unconformities at visible and radar wavelengths. According to the terrestrial classification, this approach constrains the stratigraphy of the region and remedies the ambiguous interpretation of stratigraphy through marker layers, bypassing the problem related to the morphologic and radiometric appearance of the layers. Thus, the approach does not exclude diverse classifications, but complements them, whereas other discriminant elements are doubtful or difficult/impossible to be defined. Using this approach, we defined two stratigraphic units (or synthems: PL1 and PL2) in PL, which are morphologically different and divided by a regional unconformity (AuR1). This stratigraphic architecture implies that the geological history of PL has been conditioned by periodic changes in climate, which in turn are related to orbital variations of Mars.

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Imprecise manipulation of source code (semi-parsing) is useful for tasks such as robust parsing, error recovery, lexical analysis, and rapid development of parsers for data extraction. An island grammar precisely defines only a subset of a language syntax (islands), while the rest of the syntax (water) is defined imprecisely. Usually, water is defined as the negation of islands. Albeit simple, such a definition of water is naive and impedes composition of islands. When developing an island grammar, sooner or later a programmer has to create water tailored to each individual island. Such an approach is fragile, however, because water can change with any change of a grammar. It is time-consuming, because water is defined manually by a programmer and not automatically. Finally, an island surrounded by water cannot be reused because water has to be defined for every grammar individually. In this paper we propose a new technique of island parsing - bounded seas. Bounded seas are composable, robust, reusable and easy to use because island-specific water is created automatically. We integrated bounded seas into a parser combinator framework as a demonstration of their composability and reusability.

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In this work we devise two novel algorithms for blind deconvolution based on a family of logarithmic image priors. In contrast to recent approaches, we consider a minimalistic formulation of the blind deconvolution problem where there are only two energy terms: a least-squares term for the data fidelity and an image prior based on a lower-bounded logarithm of the norm of the image gradients. We show that this energy formulation is sufficient to achieve the state of the art in blind deconvolution with a good margin over previous methods. Much of the performance is due to the chosen prior. On the one hand, this prior is very effective in favoring sparsity of the image gradients. On the other hand, this prior is non convex. Therefore, solutions that can deal effectively with local minima of the energy become necessary. We devise two iterative minimization algorithms that at each iteration solve convex problems: one obtained via the primal-dual approach and one via majorization-minimization. While the former is computationally efficient, the latter achieves state-of-the-art performance on a public dataset.

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This article provides an importance sampling algorithm for computing the probability of ruin with recuperation of a spectrally negative Lévy risk process with light-tailed downwards jumps. Ruin with recuperation corresponds to the following double passage event: for some t∈(0,∞)t∈(0,∞), the risk process starting at level x∈[0,∞)x∈[0,∞) falls below the null level during the period [0,t][0,t] and returns above the null level at the end of the period tt. The proposed Monte Carlo estimator is logarithmic efficient, as t,x→∞t,x→∞, when y=t/xy=t/x is constant and below a certain bound.

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Abstract Imprecise manipulation of source code (semi-parsing) is useful for tasks such as robust parsing, error recovery, lexical analysis, and rapid development of parsers for data extraction. An island grammar precisely defines only a subset of a language syntax (islands), while the rest of the syntax (water) is defined imprecisely. Usually water is defined as the negation of islands. Albeit simple, such a definition of water is naive and impedes composition of islands. When developing an island grammar, sooner or later a language engineer has to create water tailored to each individual island. Such an approach is fragile, because water can change with any change of a grammar. It is time-consuming, because water is defined manually by an engineer and not automatically. Finally, an island surrounded by water cannot be reused because water has to be defined for every grammar individually. In this paper we propose a new technique of island parsing —- bounded seas. Bounded seas are composable, robust, reusable and easy to use because island-specific water is created automatically. Our work focuses on applications of island parsing to data extraction from source code. We have integrated bounded seas into a parser combinator framework as a demonstration of their composability and reusability.