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Academic literature on the topic 'BRANCHING PARTICLE FILTER'

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Published: 11 September 2023

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Journal articles on the topic "BRANCHING PARTICLE FILTER"

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Crisan, Dan, and Salvador Ortiz-Latorre. "A Kusuoka–Lyons–Victoir particle filter." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 469, no. 2156 (August 8, 2013): 20130076. http://dx.doi.org/10.1098/rspa.2013.0076.

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The aim of this paper is to introduce a new numerical algorithm for solving the continuous time nonlinear filtering problem. In particular, we present a particle filter that combines the Kusuoka–Lyons–Victoir (KLV) cubature method on Wiener space to approximate the law of the signal with a minimal variance ‘thinning’ method, called the tree-based branching algorithm (TBBA) to keep the size of the cubature tree constant in time. The novelty of our approach resides in the adaptation of the TBBA algorithm to simultaneously control the computational effort and incorporate the observation data into the system. We provide the rate of convergence of the approximating particle filter in terms of the computational effort (number of particles) and the discretization grid mesh. Finally, we test the performance of the new algorithm on a benchmark problem (the Beneš filter).
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YEONG, HOONG CHIEH, JUN HYUN PARK, and N. SRI NAMACHCHIVAYA. "PARTICLE FILTERS IN A MULTISCALE ENVIRONMENT: WITH APPLICATION TO THE LORENZ-96 ATMOSPHERIC MODEL." Stochastics and Dynamics 11, no. 02n03 (September 2011): 569–91. http://dx.doi.org/10.1142/s0219493711003450.

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The study of random dynamical systems involves understanding the evolution of state variables that contain uncertainties and that are usually hidden, or not directly observable. Therefore, state variables have to be estimated and updated based on system models using information from observational data, which themselves are noisy, in the sense that they contain uncertainties and disturbances due to imperfections in observational devices and disturbances in the environment within which data are being collected. The development of efficient data assimilation methods for integrating observational data in predicting the evolution of random state variables is thus an important aspect in the study of random dynamical systems. In this paper, we consider a particle filtering approach to nonlinear filtering in multiscale dynamical systems. Particle filtering methods [1–3] utilizes ensembles of particles to represent the conditional density of state variables using particle positions, distributed over a sample space. The distribution of an ensemble of particles is updated using observational data to obtain the best representation of the conditional density of the state variables of interest. On the other hand, homogenization theory [4, 5], allows us to estimate the coarse-grained (slow) dynamics of a multiscale system on a larger timescale without having to explicitly study the fast variable evolution on a small timescale. The results of filter convergence presented in [6] shows the convergence of the filter of the actual state variable to a homogenized solution to the original multiscale system, and thus we develop a particle filtering scheme for multiscale random dynamical systems that utilizes this convergence result. This particle filtering method is called the Homogenized Hybird Particle Filter, and it incorporates a multiscale computation scheme, the Heterogeneous Multiscale Method developed in [7], with the novel branching particle filter described in [8–10]. By incorporating a multiscale scheme based on homogenization of the original system, estimation of the coarse-grained dynamics using observational data is performed over a larger timescale, thus resulting in computational time and cost reduction in terms of the evolution of the state variables as well as functional evaluations for the filtering aspect. We describe the theory behind this combined scheme and its general algorithm, concluded with an application to the Lorenz-96 [11] atmospheric model that mimics midlatitude geophysical dynamics with microscopic convective processes.
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Nakagawa, Hidetoshi, and Hideyuki Takada. "Numerical analysis of rating transition matrix depending on latent macro factor via nonlinear particle filter method." Journal of Financial Engineering 01, no. 03 (September 2014): 1450026. http://dx.doi.org/10.1142/s2345768614500263.

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We propose a new nonlinear filtering model for a better estimation of credit rating transition matrix consistent with the hypothesis that rating transition intensities as well as dynamics of financial asset prices depend on some unobservable macroeconomic factor. We attempt a branching particle filter method to numerically obtain the conditional distribution of the latent factor. For an illustration, we analyze a rating transition history of Japanese enterprises. As a result, we realize that our model can capture some contagion effect of credit events and an interpolative role of financial market information on the rating transition intensities.
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Jeon, Byunghwan. "Deep Recursive Bayesian Tracking for Fully Automatic Centerline Extraction of Coronary Arteries in CT Images." Sensors 21, no. 18 (September 10, 2021): 6087. http://dx.doi.org/10.3390/s21186087.

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Extraction of coronary arteries in coronary computed tomography (CT) angiography is a prerequisite for the quantification of coronary lesions. In this study, we propose a tracking method combining a deep convolutional neural network (DNN) and particle filtering method to identify the trajectories from the coronary ostium to each distal end from 3D CT images. The particle filter, as a non-linear approximator, is an appropriate tracking framework for such thin and elongated structures; however, the robust ‘vesselness’ measurement is essential for extracting coronary centerlines. Importantly, we employed the DNN to robustly measure the vesselness using patch images, and we integrated softmax values to the likelihood function in our particle filtering framework. Tangent patches represent cross-sections of coronary arteries of circular shapes. Thus, 2D tangent patches are assumed to include enough features of coronary arteries, and the use of 2D patches significantly reduces computational complexity. Because coronary vasculature has multiple bifurcations, we also modeled a method to detect branching sites by clustering the particle locations. The proposed method is compared with three commercial workstations and two conventional methods from the academic literature.
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Saraiev, Olexii, and Alexander Khrulev. "Devising a model of the airflow with dust particles in the intake system of a vehicle’s internal combustion engine." Eastern-European Journal of Enterprise Technologies 2, no. 1 (110) (April 20, 2021): 61–69. http://dx.doi.org/10.15587/1729-4061.2021.230113.

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This paper considers the mechanism of malfunction of internal combustion engines that implies the accelerated local wear of parts in individual cylinders as a result of uneven distribution of dust particles that pass through the air filter in the intake system. In order to acquire quantitative data on the effect of the structure of the intake system on the redistribution of dust in engine cylinders, the two-phase flow of air with dust particles in the standard elements of the intake system was mathematically modeled. ANSYS software package was used to solve the problem. A simulation technique was devised in which the airflow was first calculated to determine the boundary conditions for dust, after which the flow of air with particles was calculated. The calculations were carried out in a range of air velocities of 5‒20 m/s in branching channels with diversion angles of 45°, 90°, and 135° for the most characteristic particle sizes of 5‒30 µm. It has been estimated that dust particles deviate from the air streamlines by inertia and can slip through the lateral drain the stronger the larger particle size, diversion angle, and velocity of air. The comparison of the simulation results with experimental data confirmed that in the intake system of some engines, due to uneven particle distribution, there is local abrasive wear in one or more cylinders, which can significantly reduce the resource. This paper shows the need to take into consideration the centrifugation and redistribution of dust in the intake systems during the design, modernization, expert studies to determine the causes of faults associated with faulty operating conditions, as well as to clarify the regulations for the maintenance of existing engines.
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Meusinger, Carl, Ulrike Dusek, Stephanie M. King, Rupert Holzinger, Thomas Rosenørn, Peter Sperlich, Maxime Julien, et al. "Chemical and isotopic composition of secondary organic aerosol generated by <i>α</i>-pinene ozonolysis." Atmospheric Chemistry and Physics 17, no. 10 (May 29, 2017): 6373–91. http://dx.doi.org/10.5194/acp-17-6373-2017.

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Abstract. Secondary organic aerosol (SOA) plays a central role in air pollution and climate. However, the description of the sources and mechanisms leading to SOA is elusive despite decades of research. While stable isotope analysis is increasingly used to constrain sources of ambient aerosol, in many cases it is difficult to apply because neither the isotopic composition of aerosol precursors nor the fractionation of aerosol forming processes is well characterised. In this paper, SOA formation from ozonolysis of α-pinene – an important precursor and perhaps the best-known model system used in laboratory studies – was investigated using position-dependent and average determinations of 13C in α-pinene and advanced analysis of reaction products using thermal-desorption proton-transfer-reaction mass spectrometry (PTR-MS). The total carbon (TC) isotopic composition δ13C of the initial α-pinene was measured, and the δ13C of the specific carbon atom sites was determined using position-specific isotope analysis (PSIA). The PSIA analysis showed variations at individual positions from −6.9 to +10. 5 ‰ relative to the bulk composition. SOA was formed from α-pinene and ozone in a constant-flow chamber under dark, dry, and low-NOx conditions, with OH scavengers and in the absence of seed particles. The excess of ozone and long residence time in the flow chamber ensured that virtually all α-pinene had reacted. Product SOA was collected on two sequential quartz filters. The filters were analysed offline by heating them stepwise from 100 to 400 °C to desorb organic compounds that were (i) detected using PTR-MS for chemical analysis and to determine the O : C ratio, and (ii) converted to CO2 for 13C analysis. More than 400 ions in the mass range 39–800 Da were detected from the desorbed material and quantified using a PTR-MS. The largest amount desorbed at 150 °C. The O : C ratio of material from the front filter increased from 0.18 to 0.25 as the desorption temperature was raised from 100 to 250 °C. At temperatures above 250 °C, the O : C ratio of thermally desorbed material, presumably from oligomeric precursors, was constant. The observation of a number of components that occurred across the full range of desorption temperatures suggests that they are generated by thermal decomposition of oligomers. The isotopic composition of SOA was more or less independent of desorption temperature above 100 °C. TC analysis showed that SOA was enriched in 13C by 0.6–1.2 ‰ relative to the initial α-pinene. According to mass balance, gas-phase products will be depleted relative to the initial α-pinene. Accordingly, organic material on the back filters, which contain adsorbed gas-phase compounds, is depleted in 13C in TC by 0.7 ‰ relative to the initial α-pinene, and by 1.3 ‰ compared to SOA collected on the front filter. The observed difference in 13C between the gas and particle phases may arise from isotope-dependent changes in the branching ratios in the α-pinene + O3 reaction. Alternatively, some gas-phase products involve carbon atoms from highly enriched and depleted sites, as shown in the PSIA analysis, giving a non-kinetic origin to the observed fractionations. In either case, the present study suggests that the site-specific distribution of 13C in the source material itself governs the abundance of 13C in SOA.
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Kouritzin, Michael A. "Residual and stratified branching particle filters." Computational Statistics & Data Analysis 111 (July 2017): 145–65. http://dx.doi.org/10.1016/j.csda.2017.02.003.

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Kouritzin, Michael A. "Convergence rates for residual branching particle filters." Journal of Mathematical Analysis and Applications 449, no. 2 (May 2017): 1053–93. http://dx.doi.org/10.1016/j.jmaa.2016.12.046.

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Hoogenboezem, Wim, Jos G. M. van den Boogaart, Ferdinand A. Sibbing, Eddy H. R. R. Lammens, Arie Terlouw, and Jan W. M. Osse. "A New Model of Particle Retention and Branchial Sieve Adjustment in Filter-Feeding Bream (Abramis brama, Cyprinidae)." Canadian Journal of Fisheries and Aquatic Sciences 48, no. 1 (January 1, 1991): 7–18. http://dx.doi.org/10.1139/f91-002.

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A new model for filter feeding in bream (Abramis brama, Cyprinidae) is presented based on the three dimensional architecture of the branchial sieve. Transverse ridges on the upper surface of the gill arches form a system of channels in which food particles appear to be retained. These ridges are formed by a fleshy interconnection between the middle part of the gill arch and the bony parts of its gill rakers. Muscles attached to the rakers, present only on the lateral edge of the gill arch, indicate movability of the lateral bony raker element. If the fish is foraging on particles smaller than the channel diameter, movement of these gill rakers probably adjusts the sieve by reducing the channel diameter of the opposite channel. Selectivity of bream depends on available size classes of zooplanktons and changes in selectivity are attributed to adjustment of the branchial sieve. The channel model has been tested with feeding experiments and X-ray cinematography. The reconstructed paths of marked food particles show that particles follow the hypothesized path. Particle retention occurred mainly at the expected medial site of the arches. Our study strongly supports the channel model of particle retention.
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Kouritzin, Michael A., and Wei Sun. "Rates for branching particle approximations of continuous-discrete filters." Annals of Applied Probability 15, no. 4 (November 2005): 2739–72. http://dx.doi.org/10.1214/105051605000000539.

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Dissertations / Theses on the topic "BRANCHING PARTICLE FILTER"

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NISHA. "OBJECT TRACKING USING BRANCHING PARTICLE FILTERS." Thesis, 2017. http://dspace.dtu.ac.in:8080/jspui/handle/repository/16091.

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In digital video communication systems it is important that a video to be compressed, because of storing capacities as well as bit-rate constraints. The video processing is done using Sum of absolute Differences and with the image processing block set. We first calculate motion vectors between successive frames and use them to reduce redundant information. The method uses optical flow algorithm to calculate changes in the intensity of the pixels of the images. These apparent velocity components are then subjected to various image processing techniques to obtain centroid of the vehicle across the object. Here we are interested in finding spatio-temporal interest points of our object having a significant local variation of intensities of image. Branching particle filtering is a novel technique which is used to reduce the error in and computation time in tracking algorithm and is applied on motion frames to show these results for object detection. The distance traveled by the vehicle is calculated using the movement of the centroid over the frames. The image coordinates of the centroid are mapped to World space. The world coordinate distance is further mapped to actual distance using pixel to distance ratio. Using this information the velocity of the vehicle is estimated. In this Thesis we developed object tracking for real time video which, demonstrates the motion compensated video processing by using key point descriptor. First we have taken an object as reference object or image then the next successive object is compared with the reference object or image. Each time the successive object is compared with the reference object and produces an absolute difference then the summation of all these differences shows its sum of absolute difference.
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Book chapters on the topic "BRANCHING PARTICLE FILTER"

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Priyadarshi, Rahul, Ankush Thakur, and Anjila Deonath Singh. "Performance Evaluation Space-Time Interest Points Using Branching Particle Filters." In Lecture Notes in Electrical Engineering, 83–90. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-7091-5_8.

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Rouse, Greg W., Fredrik Pleijel, and Tilic Ekin. "PECTINARIIDAE QUATREFAGES, 1866." In Annelida, 215–18. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780199692309.003.0052.

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Pectinariidae, the aptly named ‘ice-cream cone’ worm, are an anatomically complex, if relatively uniform group that is known worldwide. They mainly occur in shallow marine sediments and are immediately recognizable from their elegant cone or tusk-shaped tubes, constructed from a single layer of sand grains, forams, shell fragments, spicules, or other particles (Pl. 11d, Figs. 52.2a, b). Adult Pectinariidae range from 10 mm to 100 mm in length and do not have more than 20 chaetigerous segments. When removed from their tubes, living Pectinariidae are translucent, with the sediment-filled gut clearly visible. The branchiae may be bright red and the distinctive anterior paleae are golden (Pl. 11d, e).
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Conference papers on the topic "BRANCHING PARTICLE FILTER"

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Ballantyne, David J., John R. Hoffman, and Michael A. Kouritzin. "Practical application of a branching particle-based nonlinear filter." In Aerospace/Defense Sensing, Simulation, and Controls, edited by Ivan Kadar. SPIE, 2001. http://dx.doi.org/10.1117/12.436953.

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Guédé, Zakoua, Alexandru Tantar, Emilia Tantar, and Pierre Del Moral. "Application of a Particle Filter-Based Subset Simulation Method to the Reliability Assessment of a Marine Structure." In ASME 2012 31st International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/omae2012-83424.

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The present study aims at investigating advanced subset simulation techniques, which are based on the theory of particle filter, for the assessment of the failure probability of a marine structure under extreme loading conditions. Three approaches are considered, namely the classical particle filter method, the subset simulation with a branching process and one using the minimum values of the samples as levels. They are, first, intensively applied on a simple example for which a known analytical solution is available, in order to investigate their parameter settings. Then, they are applied, with good performance, using their respective best parameter settings, to the assessment of failure probability of a FPSO subjected to extreme roll motion.
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Jacob, Alexsandro Machado, and Takashi Yoneyama. "A performance evaluation of branching particle filters: case studies." In XXI Simpósio Brasileiro de Telecomunicações. Sociedade Brasileira de Telecomunicações, 2004. http://dx.doi.org/10.14209/sbrt.2004.179.

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Chaudhary, Nisha, Mukesh Kumar Verma, and Saurabh Kumar Jha. "Performance Evaluation Space-Time Interest Points Using Branching Particle Filters." In 2018 International Conference on Computing, Power and Communication Technologies (GUCON). IEEE, 2018. http://dx.doi.org/10.1109/gucon.2018.8674991.

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Reports on the topic "BRANCHING PARTICLE FILTER"

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Ganzhur, Sergey F. MEASUREMENT OF B0 ---> D(S)(*)+D*- BRANCHING FRACTIONS AND POLARIZATION IN THE DECAY B0 ---> DS(*FILE) WITH A PARTIAL RECONSTRUCTION TECHNIQUE. Office of Scientific and Technical Information (OSTI), July 2002. http://dx.doi.org/10.2172/799970.

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