995 resultados para Rejection-sampling Algorithm


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Image convolution is conventionally approximated by the LTI discrete model. It is well recognized that the higher the sampling rate, the better is the approximation. However sometimes images or 3D data are only available at a lower sampling rate due to physical constraints of the imaging system. In this paper, we model the under-sampled observation as the result of combining convolution and subsampling. Because the wavelet coefficients of piecewise smooth images tend to be sparse and well modelled by tree-like structures, we propose the L0 reweighted-L2 minimization (L0RL2 ) algorithm to solve this problem. This promotes model-based sparsity by minimizing the reweighted L2 norm, which approximates the L0 norm, and by enforcing a tree model over the weights. We test the algorithm on 3 examples: a simple ring, the cameraman image and a 3D microscope dataset; and show that good results can be obtained. © 2010 IEEE.

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Changepoint models are widely used to model the heterogeneity of sequential data. We present a novel sequential Monte Carlo (SMC) online Expectation-Maximization (EM) algorithm for estimating the static parameters of such models. The SMC online EM algorithm has a cost per time which is linear in the number of particles and could be particularly important when the data is representable as a long sequence of observations, since it drastically reduces the computational requirements for implementation. We present an asymptotic analysis for the stability of the SMC estimates used in the online EM algorithm and demonstrate the performance of this scheme using both simulated and real data originating from DNA analysis.

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Changepoint models are widely used to model the heterogeneity of sequential data. We present a novel sequential Monte Carlo (SMC) online Expectation-Maximization (EM) algorithm for estimating the static parameters of such models. The SMC online EM algorithm has a cost per time which is linear in the number of particles and could be particularly important when the data is representable as a long sequence of observations, since it drastically reduces the computational requirements for implementation. We present an asymptotic analysis for the stability of the SMC estimates used in the online EM algorithm and demonstrate the performance of this scheme using both simulated and real data originating from DNA analysis.

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At present, acute vascular rejection (AVR) remains a primary obstacle inhibiting long-term graft survival in the pig-to-non-human primate transplant model. The present study was undertaken to determine whether repetitive injection of low dose Yunnan-cobra venom factor (Y-CVF), a potent complement inhibitor derived from the venom of Naja kaouthia can completely abrogate hemolytic complement activity and subsequently improve the results in a pig-to-rhesus monkey heterotopic heart transplant model. Nine adult rhesus monkeys received a heterotopic heart transplant from wild-type pigs and the recipients were allocated into two groups: group 1 (n = 4) received repetitive injection of low dose Y-CVF until the end of the study and group 2 (n = 5) did not receive Y-CVF. All recipients were treated with cyclosporine A (CsA), cyclophosphamide (CyP) and steroids. Repetitive Y-CVF treatment led to very dramatic fall in CH50 and serum C3 levels (CH50 < 3 units/C3 remained undetectable throughout the experiment) and successfully prevented hyperacute rejection (HAR), while three of five animals in group 2 underwent HAR. However, the continuous suppression of circulating complement did not prevent AVR and the grafts in group 1 survived from 8 to 13 days. Despite undetectable C3 in circulating blood, C3 deposition was present in these grafts. The venular thrombosis was the predominant histopathologic feature of AVR. We conclude that repetitive injection of low dose Y-CVF can be used to continuously suppress circulating complement in a very potent manner and successfully prevent HAR. However, this therapy did not inhibit complement deposition in the graft and failed to prevent AVR. These data suggest that using alternative pig donors [i.e. human decay accelerating factor (hDAF)-transgenic] in combination with the systemic use of complement inhibitors may be necessary to further control complement activation and improve survival in pig-to-non-human primate xenotransplant model.

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It is extremely difficult to explore mRNA folding structure by biological experiments. In this report, we use stochastic sampling and folding simulation to test the existence of the stable secondary structural units of-mRNA, look for the folding units, and explore the probabilistic stabilization of the units. Using this method, We made simulations for all possible local optimum secondary structures of a single strand mRNA within a certain range, and searched for the common parts of the secondary structures. The consensus secondary structure units (CSSUs) extracted from the above method are mainly hairpins, with a few single strands. These CSSUs suggest that the mRNA folding units could be relatively stable and could perform specific biological function. The significance of these observations for the mRNA folding problem in general is also discussed. (c) 2004 Elsevier B.V. All rights reserved.

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A control algorithm is presented that addresses the stability issues inherent to the operation of monolithic mode-locked laser diodes. It enables a continuous pulse duration tuning without any onset of Q-switching instabilities. A demonstration of the algorithm performance is presented for two radically different laser diode geometries and continuous pulse duration tuning between 0.5 ps to 2.2 ps and 1.2 ps to 10.2 ps is achieved. With practical applications in mind, this algorithm also facilitates control over performance parameters such as output power and wavelength during pulse duration tuning. The developed algorithm enables the user to harness the operational flexibility from such a laser with 'push-button' simplicity.

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The extrinsic tensile strength of glass can be determined explicitly if the characteristics of the critical surface flaw are known, or stochastically if the critical flaw characteristics are unknown. This paper makes contributions to both these approaches. Firstly it presents a unified model for determining the strength of glass explicitly, by accounting for both the inert strength limit and the sub-critical crack growth threshold. Secondly, it describes and illustrates the use of a numerical algorithm, based on the stochastic approach, that computes the characteristic tensile strength of float glass by piecewise summation of the surface stresses. The experimental validation and sensitivity analysis reported in this paper show that the proposed computer algorithm provides an accurate and efficient means of determining the characteristic strength of float glass. The algorithm is particularly useful for annealed and thermally treated float glass used in the construction industry. © 2012 Elsevier Ltd.

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Most of the manual labor needed to create the geometric building information model (BIM) of an existing facility is spent converting raw point cloud data (PCD) to a BIM description. Automating this process would drastically reduce the modeling cost. Surface extraction from PCD is a fundamental step in this process. Compact modeling of redundant points in PCD as a set of planes leads to smaller file size and fast interactive visualization on cheap hardware. Traditional approaches for smooth surface reconstruction do not explicitly model the sparse scene structure or significantly exploit the redundancy. This paper proposes a method based on sparsity-inducing optimization to address the planar surface extraction problem. Through sparse optimization, points in PCD are segmented according to their embedded linear subspaces. Within each segmented part, plane models can be estimated. Experimental results on a typical noisy PCD demonstrate the effectiveness of the algorithm.

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Engineering changes (ECs) are raised throughout the lifecycle of engineering products. A single change to one component produces knock-on effects on others necessitating additional changes. This change propagation significantly affects the development time and cost and determines the product's success. Predicting and managing such ECs is, thus, essential to companies. Some prediction tools model change propagation by algorithms, whereof a subgroup is numerical. Current numerical change propagation algorithms either do not account for the exclusion of cyclic propagation paths or are based on exhaustive searching methods. This paper presents a new matrix-calculation-based algorithm which can be applied directly to a numerical product model to analyze change propagation and support change prediction. The algorithm applies matrix multiplications on mutations of a given design structure matrix accounting for the exclusion of self-dependences and cyclic propagation paths and delivers the same results as the exhaustive search-based Trail Counting algorithm. Despite its factorial time complexity, the algorithm proves advantageous because of its straightforward matrix-based calculations which avoid exhaustive searching. Thereby, the algorithm can be implemented in established numerical programs such as Microsoft Excel which promise a wider application of the tools within and across companies along with better familiarity, usability, practicality, security, and robustness. © 1988-2012 IEEE.