Relevant bibliographies by topics / Variable structure multiple model estimation

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Variable structure multiple model estimation'

Author: Grafiati
Published: 4 June 2021
Last updated: 10 February 2022

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Journal articles on the topic "Variable structure multiple model estimation"

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Xiao-Rong Li and Y. Bar-Shalom. "Multiple-model estimation with variable structure." IEEE Transactions on Automatic Control 41, no. 4 (1996): 478–93. http://dx.doi.org/10.1109/9.489270.

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Katsikas, S. K., S. D. Likothanassis, G. N. Beligiannis, K. G. Berkeris, and D. A. Fotakis. "Genetically determined variable structure multiple model estimation." IEEE Transactions on Signal Processing 49, no. 10 (2001): 2253–61. http://dx.doi.org/10.1109/78.950781.

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Lan, Jian, X. Rong Li, and Chundi Mu. "Best Model Augmentation for Variable-Structure Multiple-Model Estimation." IEEE Transactions on Aerospace and Electronic Systems 47, no. 3 (2011): 2008–25. http://dx.doi.org/10.1109/taes.2011.5937279.

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Lan, Jian, and X. Rong Li. "Equivalent-Model Augmentation for Variable-Structure Multiple-Model Estimation." IEEE Transactions on Aerospace and Electronic Systems 49, no. 4 (2013): 2615–30. http://dx.doi.org/10.1109/taes.2013.6621840.

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Lan, Jian, and X. Rong Li. "Equivalent-Model Augmentation for Variable-Structure Multiple-Model Estimation." IEEE Transactions on Aerospace and Electronic Systems 49, no. 4 (2014): 2615–30. http://dx.doi.org/10.1109/taes.2014.6619952.

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Rong Li, X. "Multiple-model estimation with variable structure. II. Model-set adaptation." IEEE Transactions on Automatic Control 45, no. 11 (2000): 2047–60. http://dx.doi.org/10.1109/9.887626.

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Shen-tu, Han, Anke Xue, and Dongliang Peng. "Geometrical entropy approach for variable structure multiple-model estimation." Chinese Journal of Aeronautics 28, no. 4 (2015): 1131–46. http://dx.doi.org/10.1016/j.cja.2015.06.006.

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X Rong Li, Xiaorong Zwi, and Youmin Zwang. "Multiple-model estimation with variable structure. III. Model-group switching algorithm." IEEE Transactions on Aerospace and Electronic Systems 35, no. 1 (1999): 225–41. http://dx.doi.org/10.1109/7.745694.

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Rong Li, X., and Youmin Zhang. "Multiple-model estimation with variable structure. V. Likely-model set algorithm." IEEE Transactions on Aerospace and Electronic Systems 36, no. 2 (2000): 448–66. http://dx.doi.org/10.1109/7.845222.

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Li, X. Rong, Vesselin P. Jilkov, Jifeng Ru, and Anwer Bashi. "EXPECTED-MODE AUGMENTATION ALGORITHMS FOR VARIABLE-STRUCTURE MULTIPLE-MODEL ESTIMATION." IFAC Proceedings Volumes 35, no. 1 (2002): 175–80. http://dx.doi.org/10.3182/20020721-6-es-1901.00440.

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Dissertations / Theses on the topic "Variable structure multiple model estimation"

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Ru, Jifeng. "Adaptive estimation and detection techniques with applications." ScholarWorks@UNO, 2005. http://louisdl.louislibraries.org/u?/NOD,285.

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Thesis (Ph. D.)--University of New Orleans, 2005.<br>Title from electronic submission form. "A dissertation ... in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Engineering and Applied Science"--Dissertation t.p. Vita. Includes bibliographical references.
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Alat, Gokcen. "A Variable Structure - Autonomous - Interacting Multiple Model Ground Target Tracking Algorithm In Dense Clutter." Phd thesis, METU, 2013. http://etd.lib.metu.edu.tr/upload/12615512/index.pdf.

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Tracking of a single ground target using GMTI radar detections is considered. A Variable Structure- Autonomous- Interactive Multiple Model (VS-A-IMM) structure is developed to address challenges of ground target tracking, while maintaining an acceptable level computational complexity at the same time. The following approach is used in this thesis: Use simple tracker structures<br>incorporate a priori information such as topographic constraints, road maps as much as possible<br>use enhanced gating techniques to minimize the eect of clutter<br>develop methods against stop-move motion and hide mo
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Tu, Fu-Tsai, and 涂富財. "ARX Estimation Model Based Integral Variable Structure Control." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/79526545155775224302.

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碩士<br>義守大學<br>電機工程學系<br>90<br>The objective of this thesis is to design an integral variable structure control (IVSC) rule. The IVSC rule is used to handle the control of systems with external disturbances or uncertainly systems. The method can be divided into two parts. The first part is a traditional variable structure control. It is used to against modeling error and external disturbance. The other one is the use of integral controller that is used to eliminate steady state error. To obtain the mathematical model of controlled plant previously is necessary while designing its controller. Th
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Cornick, Jorge. "Estimating structural models with multiple censored variables an application to the U.S. dairy sector /." 1993. http://catalog.hathitrust.org/api/volumes/oclc/29551885.html.

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Thesis (Ph. D.)--University of Wisconsin--Madison, 1993.<br>Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 177-182).
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"Multiple comparison procedures for a latent variable model with bivariate ordered categorical responses." 2012. http://library.cuhk.edu.hk/record=b5549561.

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在許多實驗研究中，實驗數據經常由有序觀測數據組成，這樣的例子很容易在醫學、臨床研究、社會學或心理學的研究中找到。一般有兩種方法可以用來分析有序分類數據。第一種方法是基於Wilcoxon-Mann-Whitney 統計量的非參數方法，第二種方法是把響應變量看成是某個連續潛變量模型的一種表現的潛變量模型。在本論文中，我們主要研究基於潛變量模型對具有一維或二維有序分類響應變量的處理的比較問題，同時解決具有一維有序分類數據的多重比較過程的功效及樣本量的確定問題。<br>潛變量模型已經被應用于對具有一維有序分類觀測數據的含有對照組的多重比較中。這種方法可以很好地應用于臨床研究中對含有對照組的不同治療方法的效用比較問題。在本論文的第一部份中，我們致力於把這種思想推廣到成對多重比較，成對多重比較是臨床研究中另一個很重要的課題。我們通過隨機模擬來對不同的方法在控制整體第一類錯誤和功效的優勢進行評估。在本論文的第二部份，我們主要研究具有二維有序分類響應變量的多重比較過程。在這些過程中，我們把二維有序分類數據看成是某個潛二維變量的一種表現。非參數方法也經常被應用於做兩個處理的比較問題。然而在本文中，我們對非參數方法的劣勢進行了說明。處理具有二維有序分類響應變量的含有對照組的多重比較問題是本論文的研究重點。基於潛變量模型的方法，我們給出了含有對照組的多重比較的若干檢驗過程，包括單步檢驗過程和逐步檢驗過程
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Xu, Ganggang. "Variable Selection and Function Estimation Using Penalized Methods." Thesis, 2011. http://hdl.handle.net/1969.1/ETD-TAMU-2011-12-10451.

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Penalized methods are becoming more and more popular in statistical research. This dissertation research covers two major aspects of applications of penalized methods: variable selection and nonparametric function estimation. The following two paragraphs give brief introductions to each of the two topics. Infinite variance autoregressive models are important for modeling heavy-tailed time series. We use a penalty method to conduct model selection for autoregressive models with innovations in the domain of attraction of a stable law indexed by alpha is an element of (0, 2). We show that by com
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Books on the topic "Variable structure multiple model estimation"

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Babeshko, Lyudmila, and Irina Orlova. Econometrics and econometric modeling in Excel and R. INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1079837.

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The textbook includes topics of modern econometrics, often used in economic research. Some aspects of multiple regression models related to the problem of multicollinearity and models with a discrete dependent variable are considered, including methods for their estimation, analysis, and application. A significant place is given to the analysis of models of one-dimensional and multidimensional time series. Modern ideas about the deterministic and stochastic nature of the trend are considered. Methods of statistical identification of the trend type are studied. Attention is paid to the evaluati
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Babeshko, Lyudmila, Mihail Bich, and Irina Orlova. Econometrics and econometric modeling. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1141216.

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The textbook covers a wide range of issues related to econometric modeling. Regression models are the core of econometric modeling, so the issues of their evaluation, testing of assumptions, adjustment and verification are given a significant place. Various aspects of multiple regression models are included: multicollinearity, dummy variables, and lag structure of variables. Methods of linearization and estimation of nonlinear models are considered. An apparatus for evaluating systems of simultaneous and apparently unrelated equations is presented. Attention is paid to time series models. Deta
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Makatjane, Katleho, and Roscoe van Wyk. Identifying structural changes in the exchange rates of South Africa as a regime-switching process. UNU-WIDER, 2020. http://dx.doi.org/10.35188/unu-wider/2020/919-8.

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Exchange rate volatility is said to exemplify the economic health of a country. Exchange rate break points (known as structural breaks) have a momentous impact on the macroeconomy of a country. Nonetheless, this country study makes use of both unsupervised and supervised machine learning algorithms to classify structural changes as regime shifts in real exchange rates in South Africa. Weekly data for the period January 2003–June 2020 are used. To these data we apply both non-linear principal component analysis and Markov-switching generalized autoregressive conditional heteroscedasticity. The
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Book chapters on the topic "Variable structure multiple model estimation"

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"Fully Semiparametric Estimation of the Two-Parameter Latent Trait Model for Binary D a ta." In Latent Variable and Latent Structure Models. Psychology Press, 2014. http://dx.doi.org/10.4324/9781410602961-10.

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Schiller, Gregory J., and Peter S. Maybeck. "SPACE STRUCTURE CONTROL USING MULTIPLE MODEL ADAPTIVE ESTIMATION AND CONTROL." In Automatic Control in Aerospace 1994 (Aerospace Control '94). Elsevier, 1995. http://dx.doi.org/10.1016/b978-0-08-042238-1.50037-9.

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"An improvement to Variable-Structure Multiple-Model algorithm for maneuvering target tracking." In Innovation in Design, Communication and Engineering. CRC Press, 2015. http://dx.doi.org/10.1201/b18737-40.

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Manglik, Monika, Mangey Ram, and Divya Ahluwalia. "A Study of Flexible Manufacturing System With Multiple Failures." In Advanced Numerical Simulations in Mechanical Engineering. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-3722-9.ch006.

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Flexibility refers to the capability of a manufacturing system to respond cost effectively and arbitrarily to adapting production needs and necessities. This ability is becoming increasingly important for the design and operation of manufacturing systems, as these systems do function in highly variable and unpredictable environments. In this chapter, the reliability of the flexible manufacturing system has been calculated based on the mathematical framework. The model of the system consists of the system structure and the distribution of its components. The components are assumed to be repairable after various types of failures. In this work, the reliability and availability have been analyzed by using Markov process, Laplace transformations and supplementary variable techniques. Furthermore, the impacts of various failures on reliability, and availability of the system have also been analyzed.
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Zinn-Justin, Jean. "O(2) spin model and the Kosterlitz–Thouless’s phase transition." In Quantum Field Theory and Critical Phenomena. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780198834625.003.0031.

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At low temperature, the large distance properties of the O(2) spin lattice model can be described by the O(2) non-linear σ-model. The latter model is free and massless in two dimensions. The origin of this peculiarity can be found in the local structure of the field manifold: for N = 2, the O(N) sphere reduces to a circle, which cannot be distinguished locally from a straight line. Because the physical fields are sin θ or cos θ, or equivalently e<sup>± iθ</sup>, instead of θ, a field renormalization is necessary, and temperature-dependent anomalous dimensions are generated. However, the free θ action cannot describe the long-distance properties of the lattice model for all temperatures, since a high temperature analysis of the corresponding spin model shows that the correlation length is finite at high temperature, and thus a phase transition is required. In fact, it is necessary to take into account the property that θ is a cyclic variable. This condition is irrelevant at low temperature, but when the temperature increases, classical configurations with singularities at isolated points, around which θ varies by a multiple of 2π become important. The action of these configurations (vortices) can be identified with the energy of a neutral Coulomb gas, which exhibits a transition between a low temperature of bound neutral molecules and a high temperature phase of a plasma of free charges. The Coulomb gas can be mapped onto the sine-Gordon (sG) model, mapping in which the low- and high-temperature regions of the models are exchanged. This correspondence helps to understand some properties of the famous Kosterlitz-Thouless (KT) phase transition, which separates an infinite correlation length phase without order, the low-temperature phase of the O(2) spin model, from a finite correlation length phase, the high-temperature phase of the O(2) spin model.
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Yu, Ting. "Distributed Intelligence for Constructing Economic Models." In Machine Learning. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-60960-818-7.ch602.

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This paper presents an integrated and distributed intelligent system being capable of automatically estimating and updating large-size economic models. The input-output model of economics uses a matrix representation of a nation’s (or a region’s) economy to predict the effect of changes in one industry on others and by consumers, government, and foreign suppliers on the economy (Miller &amp; Blair, 1985). To construct the model reflecting the underlying industry structure faithfully, multiple sources of data are collected and integrated together. The system in this paper facilitates this estimation process by integrating a series of components with the purposes of data retrieval, data integration, machine learning, and quality checking. More importantly, the complexity of national economy leads to extremely large-size models to represent every detail of an economy, which requires the system to have the capacity for processing large amounts of data. This paper demonstrates that the major bottleneck is the memory allocation, and to include more memory, the machine learning component is built on a distributed platform and constructs the matrix by analyzing historical and spatial data simultaneously. This system is the first distributed matrix estimation package for such a large-size economic matrix.
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"Community Ecology of Stream Fishes: Concepts, Approaches, and Techniques." In Community Ecology of Stream Fishes: Concepts, Approaches, and Techniques, edited by Nicholas E. Jones, Garry J. Scrimgeour, and William M. Tonn. American Fisheries Society, 2010. http://dx.doi.org/10.47886/9781934874141.ch7.

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&lt;em&gt;Abstract&lt;/em&gt;.—We develop a conceptual model of habitat factors, operating as filters at multiple spatial and temporal scales that structure local fish assemblages in flowing waters of Arctic North America. Following the habitat template approach, we classify streams into six types based on environmental gradients, including ice formation, flow and temperature regimes, sediment dynamics, and edaphic factors. We discuss likely mechanisms influencing Arctic stream fish assemblages among the six stream types and consider this habitat template in the context of regional and local filters. There is a general increase in species richness from the eastern Arctic to Alaska that is inversely proportional to the distance from the Beringian glacial refugium. The fish fauna of Arctic streams comprises nine different families, although 14 of 24 species (58%) are members of Salmonidae. Certain life history traits are predicted to be advantageous in a periglacial environment known for cold, impoverished environments with highly variable yet generally predictable ice conditions. Examples of adaptive traits displayed by Arctic fishes include fall spawning, relatively large egg size, longevity, habitat and diet generalists, and efficient metabolism. Life history theory predicts that periodic strategists should dominate in the Arctic environment. Nevertheless, in the face of a rapidly changing climate and increasing resource development, there is much need for additional research on relationships between the traits of Arctic stream fishes and their habitat.
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Horning, Ned, Julie A. Robinson, Eleanor J. Sterling, Woody Turner, and Sacha Spector. "Linking remote sensing with modeling." In Remote Sensing for Ecology and Conservation. Oxford University Press, 2010. http://dx.doi.org/10.1093/oso/9780199219940.003.0022.

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Conservation biologists and natural resource managers often require detailed, accurate information on natural resources or biodiversity elements such as species, landscapes, and ecosystems. Their patterns of occurrence and their responses to environmental disturbance or change are dynamic over space and time and may be mediated by complex ecological processes. In most cases, our ability to directly measure or comprehensively map biodiversity elements is limited by human or financial resources, and logistical challenges such as difficulties in accessing terrain or short field seasons. In other situations, we might want to make quantitative inferences about, say, the kinds of environments that are most suitable for the persistence of an endangered species, or the influence of landscape modification on its highest-quality habitat. In these cases, developing models that explain and predict the patterns of biodiversity elements can help provide guidance at scales and resolutions that are not available through direct measurement. For example, Goetz et al. (2007) employed lidar data to predict the bird species richness across a 5,315 ha temperate forest reserve, the Patuxent National Wildlife Refuge (PWNR) in the eastern United States. In this study, Goetz et al. derived and mapped several measures of forest canopy structure, including canopy height, and three descriptors of the vertical distribution of canopy elements. In addition to lidar, they also used optical remotely sensed data from two dates of Landsat ETM+ to derive NDVI during the growing season and the difference between the NDVI of leaf-on and leaf-off conditions (growing season versus winter). Testing three different quantitative statistical models (stepwise multiple linear regression, generalized additive models, and regression trees) to predict bird species richness, the authors used field survey data on the birds of the PWNR that were collected at a series of fixed points across the reserve as the training data for the response variable (bird species richness). To calibrate the model, they combined the habitat descriptors with the survey data, usually reserving 25 percent of the survey data to validate each model’s results.
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"Whirling Disease: Reviews and Current Topics." In Whirling Disease: Reviews and Current Topics, edited by BILLIE L. KERANS and ALEXANDER V. ZALE. American Fisheries Society, 2002. http://dx.doi.org/10.47886/9781888569377.ch14.

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&lt;EM&gt;ABSTRACT. &lt;/EM&gt;The myxosporean parasite &lt;em&gt;Myxobolus cerebralis &lt;/em&gt;is the causative agent of salmonid whirling disease. Containing its spread and limiting its effects in the Intermountain West will require judicious management programs, but such actions await a comprehensive understanding of the biology and ecology of this parasite and its hosts and how these elements interact; we do not yet know the weaknesses of this organism. To better guide efforts aimed at such an understanding, we assembled available information on the ecology of the parasite, organizing it into a conceptual model of its life cycle, to help foster understanding, focus future research, and lead eventually to a mathematical model for evaluating control measures. &lt;em&gt;Myxobolus cerebralis &lt;/em&gt;has a complex life cycle with two obligate hosts, a salmonid fish and the oligochaete &lt;em&gt;Tubifex tubifex&lt;/em&gt;, parasitized by the myxosporean and the actinosporean, respectively, and two infective “spore” stages, the myxospore and the triactinomyxon. This complexity is enhanced by the variable suitability of multiple salmonid species to serve as hosts, varying host suitability of genetic variants of &lt;em&gt;T. tubifex&lt;/em&gt;, relatively recent introduction of &lt;em&gt;M. cerebralis &lt;/em&gt;to North America, and unique traits of the parasite that preclude easy classification into conventional modeling categories. Much is known about the anatomy and function of myxospores and triactinomyxons from laboratory studies, but information on their distribution, abundance, and dispersal in natural systems is limited and based on indirect observations. Similarly, we understand development of the parasite within its hosts and resulting pathologies well but know little about host immune reactions and other mechanisms controlling proliferation within hosts or how environmental factors affect these defenses. Population-level effects on fish in natural systems have been quantified only rarely, where good prewhirling disease data exist, and effects on &lt;em&gt;T. tubifex &lt;/em&gt;populations are unknown. Most rates and frequencies needed to infer relationships and model system dynamics have not been directly quantified in natural systems, but rapid progress is being made. Larger issues, including effects of &lt;em&gt;M. cerebralis &lt;/em&gt;on community dynamics and ecosystem structure and function, have yet to be explored.
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Conference papers on the topic "Variable structure multiple model estimation"

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Li, X. Rong, and Youmin Zhang. "Multiple-model estimation with variable structure: likely model set algorithm." In Aerospace/Defense Sensing and Controls, edited by Oliver E. Drummond. SPIE, 1998. http://dx.doi.org/10.1117/12.324623.

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Li, X., Xiaorong Zhi, Youmin Zhang, X. Li, Xiaorong Zhi, and Youmin Zhang. "Model-group switching algorithm for multiple-model estimation with variable structure." In Guidance, Navigation, and Control Conference. American Institute of Aeronautics and Astronautics, 1997. http://dx.doi.org/10.2514/6.1997-3453.

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Sun, Fuming, E. Xu, and Hongyu Ma. "Model-Groups Design Methods for Multiple-Model Estimation with Variable Structure." In 2008 IEEE International Symposium on Knowledge Acquisition and Modeling Workshop (KAM 2008 Workshop). IEEE, 2008. http://dx.doi.org/10.1109/kamw.2008.4810521.

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Han Shen-tu, Han Shen-tu, Anke Xue Anke Xue, and Dongliang Peng Dongliang Peng. "A minimum geometrical entropy approach for variable structure multiple-model estimation." In IET International Radar Conference 2015. Institution of Engineering and Technology, 2015. http://dx.doi.org/10.1049/cp.2015.1447.

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Yang, BaiSheng, and Hongbing Ji. "Multiple-Model Estimation for Hybrid System with Reweighted Variable Structure IMM Algorithm." In Proceedings of the International Conference. World Scientific Publishing Company, 2008. http://dx.doi.org/10.1142/9789812799524_0089.

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Li, X. Rong, Youmin Zhang, and Xiaorong Zhi. "Design and evaluation of a model-group switching algorithm for multiple-model estimation with variable structure." In Optical Science, Engineering and Instrumentation '97, edited by Oliver E. Drummond. SPIE, 1997. http://dx.doi.org/10.1117/12.283966.

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Zhang, Jiaqi, Meng Wang, Qinchi Li, Sen Wang, Xiaojun Chang, and Beilun Wang. "Quadratic Sparse Gaussian Graphical Model Estimation Method for Massive Variables." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/410.

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We consider the problem of estimating a sparse Gaussian Graphical Model with a special graph topological structure and more than a million variables. Most previous scalable estimators still contain expensive calculation steps (e.g., matrix inversion or Hessian matrix calculation) and become infeasible in high-dimensional scenarios, where p (number of variables) is larger than n (number of samples). To overcome this challenge, we propose a novel method, called Fast and Scalable Inverse Covariance Estimator by Thresholding (FST). FST first obtains a graph structure by applying a generalized thre
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Attari, Mina, Hamed Hossein Afshari, and Saeid Habibi. "Maneuvering Car Tracking Using the Interacting Multiple Model and the Dynamic 2nd-Order SVSF Method." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-47375.

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Car tracking algorithms have recently found a major role in intelligent automotive applications. They are mainly based on the state estimation techniques to solve the maneuvering car tracking problems. The dynamic 2nd-order SVSF method is a novel robust state estimation method that is based on the variable structure control theory. It benefits from the accuracy, robustness, and chattering suppression properties of second-order sliding mode systems for robust state estimation. The main contribution of this paper is to present and implement a new tracking strategy that is a combination of the dy
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Senba, Atsuhiko, and Hiroshi Furuya. "Self-Identification Experiments Using Variable Inertia Systems for Flexible Beam Structures." In ASME 2006 International Mechanical Engineering Congress and Exposition. ASMEDC, 2006. http://dx.doi.org/10.1115/imece2006-14286.

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The concept of self-identification and its feasibility are experimentally investigated. The modal parameters changed multiple times by the control input of variable inertia parameter are used to obtain linear equations about unknown structural parameters to overcome the lack of modes. We derive the controllability of the modal parameters as the requested conditions for implementing self-identification using sensitivity analyses of the modal parameters with respect to the control input. Also, a criterion for the self-identification is proposed to measure the controllability. Then, the self-iden
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Ghafarirad, Hamed, Seyed Mehdi Rezaei, Amir Abdullah, Mohammad Zareinejad, and Mozafar Saadat. "Observer-Based Robust Control With Adaptive Perturbation Estimation for a Piezoelectric Actuator." In ASME 2010 International Mechanical Engineering Congress and Exposition. ASMEDC, 2010. http://dx.doi.org/10.1115/imece2010-40167.

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Control of piezoelectric actuators is under the effects of hysteresis that could affect actuators micropositioning accuracy. In this paper a modified Prandtl-Ishlinskii (PI) operator and its inverse is utilized for both identification and real time compensation of the hysteresis effect. As a result, the actuator dynamic model would be transformed to the second order linear dynamic model. Considering the parametric uncertainties, PI estimation error and probably unmodeled dynamics, a variable structure controller coupled with adaptive perturbation estimation is proposed for trajectory tracking
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Reports on the topic "Variable structure multiple model estimation"

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Clarke, Paul S., Tom M. Palmer, and Frank Windmeijer. Estimating structural mean models with multiple instrumental variables using the generalised method of moments. Institute for Fiscal Studies, 2011. http://dx.doi.org/10.1920/wp.cem.2011.2811.

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