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arXiv 2024年

作者： Liu, Peng Li, Kailai Hendeby, Gustaf Gustafsson, Fredrik Division of Automatic Control Department of Electrical Engineering Linköping University Linköping Sweden Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence University of Groningen Groningen Netherlands

This letter proposes a new method for joint state and parameter estimation in uncertain dynamical systems. We exploit the partial errors-in-variables (PEIV) principle and formulate a regression problem in the sense of weighted total least squares, where the uncertainty in the parameter prior is explicitly considered. Based thereon, the PEIV regression can be solved iteratively through the Kalman smoothing and the regularized least squares for estimating the state and the parameter, respectively. The simulations demonstrate improved accuracy of the proposed method compared to existing approaches, including the joint maximum a posterior-maximum likelihood, the expectation maximisation, and the augmented state extended Kalman smoother. Copyright © 2024, The Authors. All rights reserved.

关键词： Errors

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Texture Analysis of Breast US Images Using Morphological Transforms, Hausdorff Dimension and Bagging Ensemble Method 32

Texture Analysis of Breast US Images Using Morphological Tra...

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32nd Mediterranean Conference on control and Automation, MED 2024

作者： Tabacaru, Gigi Moldovanu, Simona Barbu, Marian 'Dunarea de Jos' University of Galati Faculty of Automation Computers Electrical Engineering and Electronics Department of Automatic Control and Electrical Engineering Romania 'Dunarea de Jos' University of Galati Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics Romania Dunarea de Jos University of Galati The Modelling & Simulation Laboratory Galati800008 Romania

ISBN: (纸本)9798350395440

In this work, an attempt is made for the first time to use the measurement pattern generated by morphological transformation quantified by Hausdorff fractal dimension (HFD) and classified with ensemble learning based on bagging. The proposed work uses three morphological transformations for image preprocessing: hit-and-miss transform (HMT), white (WHT), and black top-hat (BHT). The pattern texture of US breast images is described by extracting the HFD from the regions of interest (ROI) after the ultrasound (US) images have been preprocessed. The main objective of this study was achieved by comparatively analyzing the classification performance of features using the Random Forest (RF), Extra Trees (ET) classifier, and bagging ensemble method based on XGBoot classifier. In presented study, the XGBoost classifier and BHT image processing method give an accuracy of 89.8% in a binary classification, benign versus malignant breast cancer. © 2024 IEEE.

关键词： Fractal dimension

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Ante-Hoc Generation of Task-Agnostic Interpretation Maps

Ante-Hoc Generation of Task-Agnostic Interpretation Maps

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IEEE computer Society Conference on computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Akash Guna R T Raul Benitez Sikha O K Department of Computer Science and Engineering Amrita School of Engineering Coimbatore India Departament of Automatic Control Universitat Politècnica de Catalunya-BarcelonaTech Spain

Existing explainability approaches for convolutional neural networks (CNNs) are mainly applied after training (post-hoc) which is generally unreliable. Ante-hoc explainers trained simultaneously with the CNN are more reliable. However, current ante-hoc explanation methods mainly generate inexplicit concept-based explanations tailored to specific tasks. To address these limitations, we propose a task-agnostic ante-hoc framework that can generate interpretation maps to visually explain any CNN. Our framework simultaneously trains the CNN and a weighting network - an explanation generation module. The generated maps are self-explanatory, eliminating the need for manual identification of concepts. We demonstrate that our method can interpret classification, facial landmark detection, and image captioning tasks. We show that our framework is explicit, faithful, and stable through experiments. To the best of our knowledge, this is the first ante-hoc CNN explanation strategy that produces visual explanations generic to CNNs for different tasks.

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NPC type three-level inverter open circuit fault diagnosis based on data driven

NPC type three-level inverter open circuit fault diagnosis b...

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第34届中国过程控制会议

作者： Tianyu Sun Chaobo Chen Shenhang Wang Binbin Zhang Yanfang Fu Song Gao TianLi Ma School of Electronic Information Engineering Xi'an Technological University Beijing Aerospace Automatic Control Institution School of Computer Science and Engineering Xi'an Technological University

The historical monitoring data of NPC type three-level inverter is ***,the feature extraction of non-stationary fault signal is *** view of the above problems,a fault diagnosis method via the combination of compressed sensing(OCS) and Wavelet Packet Decomposition(WPD) is ***,the three-phase voltage of the inverter is extracted to form a measurement *** combining the Gram matrix and the fast iterative shrinkage threshold algorithm,the measurement matrix is *** can reduce the correlation between the measurement matrix and sparse basis and improve the reconstruction of the compressed ***,considering the local anomalies and non-stationary characteristics of the fault signal,wavelet packet decomposition is used to compress the data,extract the energy of the sub-band signal,and construct feature ***,a feature dataset classifier model is established based on the Tian-Niu whisker optimization ***,the algorithm proposed in the article was validated on a simulation *** simulation results show that the proposed OCS-WPD method can effectively extract fault sensitive *** fault diagnosis model has high fault detection rate and fast diagnostic speed.

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Improving control Performance by Cascading Observers: Case of ADRC With Cascade ESO

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IEEE/CAA Journal of automatica Sinica 2024年

作者： Benyahia, Ahmed T.-E. Stanković, Momir Madonski, Rafal Babayomi, Oluleke Manojlović, Stojadin M. The Military Academy University of Defence Beograd11042 Serbia The Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice44-100 Poland The CCS Graduate School of Mobility Korea Advanced Institute of Science and Technology Daejeon Korea Republic of

In this paper, we show the performance benefits of connecting multiple observers within a control system. We focus here on a particular observer-based control approach, namely the active disturbance rejection control (ADRC) with cascade extended state observer (ESO). For this framework, we analyze the control performance in terms of quality of observer estimation, reference tracking, disturbance rejection, sensitivity to measurement noise/unmodeled dynamics, and overall stability. A comprehensive frequency response analysis is performed to study the influence of cascading the observers on the selected quality criteria. To make the inquiry beneficial also to practitioners, FPGA-in-the-loop tests are conducted using a guided missiles gimbaled seeker. They validate the theoretical findings in discrete-time settings, where the sampling time and hardware resource requirements become a factor. The results of the investigation are distilled into guidelines for prospective users on when and how a cascade observer structure can be useful for controls. © 2014 Chinese Association of Automation.

关键词： Disturbance rejection

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Maximizing social power in multiple independent Friedkin-Johnsen models

Maximizing social power in multiple independent Friedkin-Joh...

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European control Conference (ECC)

作者： Lingfei Wang Yu Xing Claudio Altafini Karl H. Johansson Division of Decision and Control Systems Digital Futures School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Electrical Engineering Division of Automatic Control Linköping University Linköping Sweden

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

This paper investigates the problem of maximizing social power for a group of agents, who participate in multiple meetings described by independent Friedkin-Johnsen models. A strategic game is obtained, in which the action of each agent (or player) is her stubbornness over all the meetings, and the payoff is her social power on average. It is proved that, for all but some strategy profiles on the boundary of the feasible action set, each agent's best response is the solution of a convex optimization problem. Furthermore, even with the non-convexity on boundary profiles, if the underlying networks are given by a fixed complete graph, the game has a unique Nash equilibrium. For this case, the best response of each agent is analytically characterized, and is achieved in finite time by a proposed algorithm.

关键词： Network topology Europe Games Nash equilibrium Cost function Convex functions

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Noise Reduction in Industry Based on Virtual Instrumentation

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computers, Materials & Continua 2021年第10期69卷 1073-1096页

作者： Radek Martinek Rene Jaros Jan Baros Lukas Danys Aleksandra Kawala-Sterniuk Jan Nedoma Zdenek Machacek Jiri Koziorek Faculty of Electrical Engineering and Computer Science Department of Cybernetics and Biomedical EngineeringVSB–Technical University of Ostrava70800Ostrava-PorubaCzechia Faculty of Electrical Engineering Automatic Control and InformaticsOpole University of TechnologyOpolePoland Faculty of Electrical Engineering and Computer Science Department of TelecommunicationsVSB–Technical University of Ostrava70800Ostrava-PorubaCzechia

This paper discusses the reduction of background noise in an industrial environment to extend *** the Industry 4.0 era,the mass development of voice control(speech recognition)in various industrial applications is possible,especially as related to augmented reality(such as hands-free control via voice commands).As Industry 4.0 relies heavily on radiofrequency technologies,some brief insight into this problem is provided,including the Internet of things(IoT)and 5G *** study was carried out in cooperation with the industrial partner Brose CZ spol.s.r.o.,where sound recordings were made to produce a *** experimental environment comprised three workplaces with background noise above 100 dB,consisting of a laser/magnetic welder and a press.A virtual device was developed from a given dataset in order to test selected commands from a commercial speech recognizer from *** tested a hybrid algorithm for noise reduction and its impact on voice command recognition *** virtual devices,the study was carried out on large speakers with 20 participants(10 men and 10 women).The experiments included a large number of repetitions(100 times for each command under different noise conditions).Statistical results confirmed the efficiency of the tested *** welding environment efficiency was 27%before applied filtering,76%using the least mean square(LMS)algorithm,and 79%using LMS+independent component analysis(ICA).Magnetic welding environment efficiency was 24%before applied filtering,70%with LMS,and 75%with LMS+*** workplace environment efficiency showed no success before applied filtering,was 52%with LMS,and was 54%with LMS+ICA.

关键词： 5G hybrid algorithms signal processing speech recognition

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Smart Solutions to Keep Your Mental Balance 9th

Smart Solutions to Keep Your Mental Balance

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9th International Conference on Information Technology and Quantitative Management, ITQM 2022

作者： Gifu, Daniela Pop, Eugen Institute of Computer Science Romanian Academy - Iasi Branch Bulevardul Carol I 8 700505 Romania Faculty of Computer Science alexandru Ioan Cuza University General Berthelot 16 Iasi700483 Romania Faculty of Automatic Control and Computers University politehnica of Bucharest Splaiul Independentei 313 Bucharest060032 Romania

Due to the coronavirus pandemic international conflicts, dramatic changes of daily living have been enforced, including new ways of providing patient assistance, based on artificial intelligence. The influence of these changes on people's mental health is still insufficiently analyzed and explored. Chatbots like Woebot, Wysa and Tess are gaining popularity, being attractive and easy to use. These achievements led us to develop a new application, being still in the testing phase, which has a positive impact on mental healthcare issues. It is a conversational system capable to diagnose people's negative, depressive, and anxious emotions during chatting, and to act as a psychological therapist and virtual friend. The proposed system, throughout the conversation, succeeds to decrease the patient's insecurity sentiments, by comforting their mood. In fact, an intelligent assistant for different mental health issues like stress, anxiety and depression, could become a very helpful information system. © 2022 The Authors. Published by Elsevier B.V.

关键词： Coronavirus

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Out-of-distribution Object Detection through Bayesian Uncertainty Estimation

arXiv

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arXiv 2023年

作者： Zhang, Tianhao Wang, Shenglin Bouaynaya, Nidhal Calinescu, Radu Mihaylova, Lyudmila Automatic Control and Systems Engineering The University of Sheffield United Kingdom Department of Electrical and Computer Engineering Rowan University United States Department of Computer Science University of York United Kingdom

The superior performance of object detectors is often established under the condition that the test samples are in the same distribution as the training data. However, in many practical applications, out-of-distribution (OOD) instances are inevitable and usually lead to uncertainty in the results. In this paper, we propose a novel, intuitive, and scalable probabilistic object detection method for OOD detection. Unlike other uncertainty-modeling methods that either require huge computational costs to infer the weight distributions or rely on model training through synthetic outlier data, our method is able to distinguish between in-distribution (ID) data and OOD data via weight parameter sampling from proposed Gaussian distributions based on pre-trained networks. We demonstrate that our Bayesian object detector can achieve satisfactory OOD identification performance by reducing the FPR95 score by up to 8.19% and increasing the AUROC score by up to 13.94% when trained on BDD100k and VOC datasets as the ID datasets and evaluated on COCO2017 dataset as the OOD dataset. Copyright © 2023, The Authors. All rights reserved.

关键词： Object detection

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Sharing the control of Robot Swarms Among Multiple Human Operators: A User Study

Sharing the Control of Robot Swarms Among Multiple Human Ope...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Genki Miyauchi Yuri K. Lopes Roderich Groß Department of Automatic Control and Systems Engineering The University of Sheffield Sheffield United Kingdom Department of Computer Science Santa Catarina State University Joinville Brazil

Simultaneously controlling multiple robot swarms is challenging for a single human operator. When involving multiple operators, however, they can each focus on controlling a specific robot swarm, which helps distribute the cognitive workload. They could also exchange some robots with each other in response to the requirements of the tasks they discover. This paper investigates the ability of multiple operators to dynamically share the control of robot swarms and the effects of different communication types on performance and human factors. A total of 52 participants completed an experiment in which they were randomly paired to form a team. In a $2\times 2$ mixed factorial study, participants were split into two groups by communication type (direct vs. indirect). Both groups experienced different robot-sharing conditions (robot-sharing vs. no-robot-sharing). Results show that although the ability to share robots did not necessarily increase task scores, it allowed the operators to switch between working independently and collaboratively, reduced the total energy consumed by the swarm, and was considered useful by the participants.

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