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UKACC International Conference on control 2010

作者： Bányász, Cs. Keviczky, L. Computer and Automation Research Institute of the H. Ac. of Sc. Control Engineering Research Group of the H. Ac. of Sc. Budapest Univ. of Technology and Economics Kende u 13-17 H-1111 Budapest Hungary

The Youla-parametrization is a useful method and widely applied to design controllers for open-loop stable single-input-singe-output (SISO) plants. The KB-parametrization is a successful extension of this method for t... 详细信息

ISBN: (纸本)9781846000386

关键词： controllers

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BAYESIAN QUBIT STATE ESTIMATION

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IFAC Proceedings Volumes 2006年第1期39卷 949-954页

作者： Attila Magyar Dénes Petz Katalin M. Hangos Process Control Research Group Computer and Automation Research Institute Budapest Hungary Alfréd Rényi Institute of Mathematics Budapest Hungary

In this paper a Bayesian approach for estimating the state of a qubit is proposed. It consists of two phases. First a component-wise separate Bayesian estimate of the Bloch vector components is calculated in the form of β -distributions. Then a regularization step is performed to respect the constraint that the Bloch vector must be in the unit ball. The properties of the proposed algorithm are investigated by simulation.

关键词： System identification Bayesian estimation quantum systems regularization

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Internal stability and loop-transformations: an overview on LFTs, Möbius transforms and chain scattering

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IFAC-PapersOnLine 2017年第1期50卷 7547-7553页

作者： Szabó Z. Seiler P. Bokor J. Institute for Computer Science and Control Hungarian Academy of Sciences Hungary Department of Aerospace Engineering and Mechanics University of Minnesota 107 Akerman Hall 110 Union St SE Minneapolis MN 55455 United States Institute for Computer Science and Control Hungarian Academy of Sciences MTA-BME Control Engineering Research Group Hungary

In robust control problems it is often convenient to consider maps between controller sets that are defined by Möbius transformations. Moreover, these loop-transformations are also intimately related to different factorizations, that simplify the structure of the problem. Starting from a fundamental observation that relates internal stability of the control loops to mere stability of a specific LFT, the paper provides an exhaustive answer to the question under which conditions the internal stability of a control loop is preserved by performing a loop-transformation. As a main result it is shown that Möbius transformations defined by unimodular matrices preserves the internal stability of the loop and an explicit formula is also given that relates the two loops. This result is formulated in a general context that includes LTV or LPV systems as well. The paper also provides an overview on the different transformation techniques, as Möbius transformations, LFTs, different generalized chain scattering (CSD) transforms, and their interrelations. This knowledge gives a solid basis for those approaches that use an input-output framework in combination with the IQC analysis and synthesis techniques in the solution of linear parameter varying (LPV) design problems. © 2017

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Tumor Detection, Segmentation and Classification Challenge on Automated 3D Breast Ultrasound: The TDSC-ABUS Challenge

arXiv

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arXiv 2025年

作者： Luo, Gongning Xu, Mingwang Chen, Hongyu Liang, Xinjie Tao, Xing Ni, Dong Jeong, Hyunsu Kim, Chulhong Stock, Raphael Baumgartner, Michael Kirchhoff, Yannick Rokuss, Maximilian Maier-Hein, Klaus Yang, Zhikai Fan, Tianyu Boutry, Nicolas Tereshchenko, Dmitry Moine, Arthur Charmetant, Maximilien Sauer, Jan Du, Hao Bai, Xiang-Hui Raikar, Vipul Pai Montoya-Del-Angel, Ricardo Martí, Robert Luna, Miguel Lee, Dongmin Qayyum, Abdul Mazher, Moona Guo, Qihui Wang, Changyan Awasthi, Navchetan Zhao, Qiaochu Wang, Wei Wang, Kuanquan Wang, Qiucheng Dong, Suyu School of Computer Science and Technology Harbin Institute of Technology Harbin150001 China Department of Mathematics Faculty of Science National University of Singapore Singapore National-Regional Key Technology Engineering Laboratory for Medical Ultrasound School of Biomedical Engineering Shenzhen University Medical School Shenzhen University Shenzhen China Laboratory Shenzhen University Shenzhen China School of Biomedical Engineering and Informatics Nanjing Medical University Nanjing China Pohang Korea Republic of Heidelberg Division of Medical Image Computing Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Germany Heidelberg Germany HIDSS4Health - Helmholtz Information and Data Science School for Health Karlsruhe Heidelberg Germany Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Germany Department of Biomedical Engineering and Health KTH Royal Institute of Technology Stockholm Sweden France FathomX Singapore Saw Swee Hock School of Public Health National University of Singapore Singapore Philips Research University of Girona Spain Department of Robotics and Mechatronics Engineering DGIST Korea Republic of Department of Interdisciplinary Studies of Artificial Intelligence DGIST Korea Republic of National Heart and Lung Institute Faculty of Medicine Imperial College London London United Kingdom Centre for Medical Image Computing Department of Computer Science University College London London United Kingdom Lab School of Communication and Information Engineering Shanghai University Shanghai China Faculty of Science Mathematics and Computer Science Informatics Institute University of Amsterdam Amsterdam1090 GH Netherlands Department of Biomedical Engineering and Physics Amsterdam UMC Amsterdam1081 HV Netherlands Xi’an Jiaotong-Liverpool University China Department of Ultrasound Harbin Medical University Cancer Hospital No. 150 Haping Road Nangang

Breast cancer is one of the most common causes of death among women worldwide. Early detection helps in reducing the number of deaths. Automated 3D Breast Ultrasound (ABUS) is a newer approach for breast screening, which has many advantages over handheld mammography such as safety, speed, and higher detection rate of breast cancer. Tumor detection, segmentation, and classification are key components in the analysis of medical images, especially challenging in the context of 3D ABUS due to the significant variability in tumor size and shape, unclear tumor boundaries, and a low signal-to-noise ratio. The lack of publicly accessible, well-labeled ABUS datasets further hinders the advancement of systems for breast tumor analysis. Addressing this gap, we have organized the inaugural Tumor Detection, Segmentation, and Classification Challenge on Automated 3D Breast Ultrasound 2023 (TDSC-ABUS2023). This initiative aims to spearhead research in this field and create a definitive benchmark for tasks associated with 3D ABUS image analysis. In this paper, we summarize the top-performing algorithms from the challenge and provide critical analysis for ABUS image examination. We offer the TDSC-ABUS challenge as an open-access platform at https://***/ to benchmark and inspire future developments in1algorithmic research. © 2025, CC BY.

关键词： Image segmentation

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Prediction-based diagnosis and loss prevention using model-based reasoning

Prediction-based diagnosis and loss prevention using model-b...

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18th International Conference on Industrial and engineering Applications of Artificial Intelligence and Expert Systems: Innovations in Applied Artificial Intelligence, IEA/AIE 2005

作者： Námeth, Erzsábet Lakner, Rozália Hangos, Katalin M. Cameron, Ian T. Systems and Control Laboratory Computer and Automation Research Institute Budapest Hungary Department of Computer Science University of Veszprám Veszprám Hungary School of Engineering University of Queensland Brisbane Australia

ISBN: (纸本)3540265511

A diagnostic expert system established on model-based reasoning for on-line diagnosis and loss prevention is described in the paper. Its diagnostic "cause-effect" rules and possible actions (suggestions) are extracted from the results of standard HAZOP analysis. Automatic focusing as well as "what-if" type reasoning for testing hypothetical actions have been also implemented. The diagnostic system is tested on a granulator drum of a fertilizer plant in a simulation test-bed. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Artificial intelligence

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Robust Stabilization of T-S Fuzzy Stochastic Descriptor Systems via Integral Sliding Modes

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IEEE TRANSACTIONS ON CYBERNETICS 2018年第9期48卷 2736-2749页

作者： Li, Jinghao Zhang, Qingling Yan, Xing-Gang Spurgeon, Sarah K. Institute of Systems Science State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China Instrumentation Control and Embedded Systems Research Group School of Engineering and Digital Arts University of Kent Canterbury U.K. Department of Electronic and Electrical Engineering University College London London U.K.

This paper addresses the robust stabilization problem for T-S fuzzy stochastic descriptor systems using an integral sliding mode control paradigm. A classical integral sliding mode control scheme and a nonparallel distributed compensation (Non-PDC) integral sliding mode control scheme are presented. It is shown that two restrictive assumptions previously adopted developing sliding mode controllers for Takagi-Sugeno (T-S) fuzzy stochastic systems are not required with the proposed framework. A unified framework for sliding mode control of T-S fuzzy systems is formulated. The proposed Non-PDC integral sliding mode control scheme encompasses existing schemes when the previously imposed assumptions hold. Stability of the sliding motion is analyzed and the sliding mode controller is parameterized in terms of the solutions of a set of linear matrix inequalities which facilitates design. The methodology is applied to an inverted pendulum model to validate the effectiveness of the results presented.

关键词： Integral sliding mode control inverted pendulum nonparallel distributed compensation (Non-PDC) robust stabilization Takagi-Sugeno (T-S) fuzzy stochastic descriptor systems

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Single landmark based self-localization of mobile robots

Single landmark based self-localization of mobile robots

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3rd Canadian Conference on computer and Robot Vision, CRV 2006

作者： Bais, Abdul Sablatnig, Robert Gu, Jason Institute of Computer Technology Vienna University of Technology Vienna Austria Pattern Recognition and Image Processing Group Institute of Computer Aided Automation Vienna University of Technology Vienna Austria Robotics Research Group Department of Electrical and Computer Engineering Dalhousie University Halifax Canada

ISBN: (纸本)0769525423

In this paper we discuss landmark based absolute localization of tiny autonomous mobile robots in a known environment. Landmark features are naturally occurring as it is not allowed to modify the environment with special navigational aids. These features are sparse in our application domain and are frequently occluded by other robots. This makes simultaneous acquisition of two or more landmarks difficult. Therefore, we propose a system that requires a single landmark feature. The algorithm is based on range measurement of a single landmark from two arbitrary points whose displacement can be measured using dead-reckoning sensors. Range estimation is done with a stereo vision system. Simulation results show that the robot can localize itself if it can estimates range of the same landmark from two different position and if the displacement between the two position is known. © 2006 IEEE.

关键词： Mobile robots

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Calcium coupled bursting in an integrative model of GnRH neuronal electrophysiology

Calcium coupled bursting in an integrative model of GnRH neu...

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作者： Csercsik, D. Farkas, I. Process Control Research Group Computer and Automation Research Institute Hungarian Academy of Sciences Hungary Department of Endocrine Neurobiology Institute of Experimental Medicine Hungarian Academy of Sciences Hungary MTA SzTAKI Kende U. 13-17 Budapest Hungary

In this paper, an integrative dynamical model of GnRH electrophysiology is used to study the calcium related interactions corresponding to bursting behavior. Various mechanisms affecting calcium dynamics are blocked or modified, and simulation results are compared to literature data to verify the model. © 2011 Springer-Verlag Berlin Heidelberg.

关键词： Electrophysiology

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Parallel Building: A Complex System Approach for Smart Building Energy Management

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IEEE/CAA Journal of Automatica Sinica 2019年第6期6卷 1452-1461页

作者： Abdulaziz Almalaq Jun Hao Jun Jason Zhang Fei-Yue Wang Department of Electrical Engineering Engineering CollegeUniversity of HailHail 55476Saudi Arabia Department of Electrical and Computer Engineering Ritchie School of Engineering and Computer ScienceUniversity of DenverDenverCO 80208 USA State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 and also with the Research Center for Military Computational Experiments and Parallel Systems TechnologyNational University of Defense TechnologyChangsha 410073China

These days' smart buildings have high intensive information and massive operational parameters, not only extensive power consumption. With the development of computation capability and future 5 G, the ACP theory(i.e., artificial systems,computational experiments, and parallel computing) will play a much more crucial role in modeling and control of complex systems like commercial and academic buildings. The necessity of making accurate predictions of energy consumption out of a large number of operational parameters has become a crucial problem in smart buildings. Previous attempts have been made to seek energy consumption predictions based on historical data in buildings. However, there are still questions about parallel building consumption prediction mechanism using a large number of operational parameters. This article proposes a novel hybrid deep learning prediction approach that utilizes long short-term memory as an encoder and gated recurrent unit as a decoder in conjunction with ACP theory. The proposed approach is tested and validated by real-world dataset, and the results outperformed traditional predictive models compared in this paper.

关键词： ACP theory artificial intelligence data acquisition deep learning(DL) energy consumption machine learning parallel energy prediction prediction algorithms smart grid

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Hierarchical modelling in biology: Systematic building of limb models

Hierarchical modelling in biology: Systematic building of li...

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作者： Fazekas, C.S. Kozmann, G.Y. Hangos, K.M. Department of Information Systems University of Veszprém Veszprém Hungary Research Institute for Technical Physics and Materials Sciences Department of Biomedical Engineering Budapest Hungary Computer and Automation Research Institute Systems and Control Laboratory Budapest Hungary

ISBN: (纸本)008045108X

A multi-level model, that provides a hierarchically structured description of a complex, multi-scale limb system is proposed in this paper for predicting and analyzing movement patters generated by various activation signals. The levels, the sub-models on each level and their interconnections are developed and described following a systematic modelling procedure. The computational properties (degree of freedom and differential index) of the developed model have been analyzed and a sub-model has been transformed to meet the index-one requirement for solving the resulting differential algebraic equation (DAE) model by standard methods implemented in MATLAB. The model is extensively verified against engineering expectations using parameter values found in the literature, and a good agreement was found. Parameter sensitivity analysis has also been performed. Copyright © 2005 IFAC.

关键词： Hierarchical systems

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