检索结果-内蒙古大学图书馆

A Primal-Dual SGD Algorithm for Distributed Nonconvex Optimization

IEEE/CAA Journal of automatica Sinica 2022年第5期9卷 812-833页

作者： Xinlei Yi Shengjun Zhang Tao Yang Tianyou Chai Karl Henrik Johansson Division of Decision and Control Systems School of Electrical Engineering and Computer ScienceKTH Royal Institute of Technologyand also affiliated with the Digital FuturesStockholm 10044Sweden Department of Electrical Engineering University of North TexasDentonTX 76203 USA IEEE State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819China

The distributed nonconvex optimization problem of minimizing a global cost function formed by a sum of n local cost functions by using local information exchange is *** problem is an important component of many machine learning techniques with data parallelism,such as deep learning and federated *** propose a distributed primal-dual stochastic gradient descent(SGD)algorithm,suitable for arbitrarily connected communication networks and any smooth(possibly nonconvex)cost *** show that the proposed algorithm achieves the linear speedup convergence rate O(1/(√nT))for general nonconvex cost functions and the linear speedup convergence rate O(1/(nT)) when the global cost function satisfies the Polyak-Lojasiewicz(P-L)condition,where T is the total number of *** also show that the output of the proposed algorithm with constant parameters linearly converges to a neighborhood of a global *** demonstrate through numerical experiments the efficiency of our algorithm in comparison with the baseline centralized SGD and recently proposed distributed SGD algorithms.

关键词： Distributed nonconvex optimization linear speedup Polyak-Lojasiewicz(P-L)condition primal-dual algorithm stochastic gradient descent

来源：评论

学校读者我要写书评

暂无评论

Wireless control of a D.C. Motor Used for Driving a Conveyor Belt

Wireless control of a D.C. Motor Used for Driving a Conveyor...

引用

2024 International Conference on Circuit, systems and Communication, ICCSC 2024

作者： Livint, Petru Banu, Ioan-Viorel Culea, George Manale, Bouderbala Majout, Btissam Dusa, Alexandru University 'Vasile Alecsandri' of Bacau Department of Energetics and Science Computer Romania Sidi Mohammed Ben Abdellah University Fez Limas Laboratory Faculty of Sciences Dhar El Mahraz Morocco Sidi Mohammed Ben Abdellah University Fez Laboratory of Engineering Modellingand Systems Analysis Morocco 'Dunarea de Jos' University of Galati Department of Automatic and Electrical Engineering Romania

ISBN: (纸本)9798350365306

This article presents an experimental stand for the remote control of a D.C. motor used to drive a conveyor belt. This is based on two development boards Arduino Uno and two shields NRF24L01. The D. C. motor is supplied from a D.C. voltage source by means of the H type bridge. The emitter circuit sends the control signal generated through a potentiometer to the receptor circuit by means of radio waves at a frequency of 2.4 GHz. The receptor circuit receives the analogue signal emitted by the emitting circuit, transforms it into a PWM (pulse width modulation) signal and uses it for controlling the transistors of the H-bridge. For implementing and validating the remote control system of the D.C. motor two programs have been issued in the programming environment Arduino IDE for the two circuits. emitter and receptor. The remote control system of the D.C. motor has been running in the same way as the direct control of this. The remote control is used in the case of the electric actuation systems made with D.C. motors continuous used in spaces inaccessible to the human operator. © 2024 IEEE.

关键词： Belts

来源：评论

学校读者我要写书评

暂无评论

Convex Equilibrium-Free Stability and Performance Analysis of Discrete-Time Nonlinear systems

arXiv

引用

arXiv 2024年

作者： Koelewijn, Patrick J.W. Weiland, Siep Tóth, Roland Control Systems Group Department of Electrical Engineering Eindhoven University of Technology Netherlands Systems and Control Laboratory HUN-REN Institute for Computer Science and Control Hungary

This paper considers the equilibrium-free stability and performance analysis of discrete-time nonlinear systems. We consider two types of equilibrium-free notions. Namely, the universal shifted concept, which considers stability and performance w.r.t. all equilibrium points of the system, and the incremental concept, which considers stability and performance between trajectories of the system. In this paper, we show how universal shifted stability and performance of discrete-time systems can be analyzed by making use of the time-difference dynamics. Moreover, we extend the existing results for incremental dissipativity for discrete-time systems based on dissipativity analysis of the differential dynamics to more general state-dependent storage functions for less conservative results. Finally, we show how both these equilibrium-free notions can be cast as a convex analysis problem by making use of the linear parameter-varying framework, which is also demonstrated by means of an example. Copyright © 2024, The Authors. All rights reserved.

关键词： Nonlinear systems

来源：评论

学校读者我要写书评

暂无评论

On the Gaussian Filtering for Nonlinear Dynamic systems Using Variational Inference 27

On the Gaussian Filtering for Nonlinear Dynamic Systems Usin...

引用

27th International Conference on Information Fusion, FUSION 2024

作者： Liu, Yi Li, Xi Yang, Le Mihaylova, Lyudmila Li, Ji University of Canterbury Department of Electrical and Computer Engineering Christchurch New Zealand National University of Defense Technology State Key Lab of Complex Electromagnetic Environment Effects on Electronics and Information Systems Changsha China University of Sheffield Department of Automatic Control and System Engineering Sheffield United Kingdom Locaris Electronic Technology Co. Ltd Zhengzhou China

ISBN: (纸本)9781737749769

This paper introduces a new variational Gaussian filtering approach for estimating the state of a nonlinear dynamic system. We first assume that the predictive distribution of the state is Gaussian and derive an iterative method for updating the state posterior in the natural parameter space through KullbackLeibler divergence minimization. The obtained update rule is the same as that of the conjugate-computation variational inference technique in Bayesian learning. The derivation here is simpler and more insightful. We then impose a Wishart prior on the inverse of the state prediction covariance to take into account the impact of approximating the state predictive distribution using a Gaussian density on the state posterior estimation. The prediction covariance is identified jointly with the state using variational inference and the established state posterior update rule to achieve the desired Gaussian filtering. Simulation study examines the performance of the proposed filtering framework in target tracking based on bearing and range measurements. © 2024 ISIF.

关键词： Wiener filtering

来源：评论

学校读者我要写书评

暂无评论

When Does Sora Show:The Beginning of TAO to Imaginative Intelligence and Scenarios engineering

引用

IEEE/CAA Journal of automatica Sinica 2024年第4期11卷 809-815页

作者： Fei-Yue Wang Qinghai Miao Lingxi Li Qinghua Ni Xuan Li Juanjuan Li Lili Fan Yonglin Tian Qing-Long Han School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China Department of Electrical and Computer Engineering Indiana University-Purdue University IndianapolisIndianapolisIN 46202USA Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China Virtual Reality Fundamental Research Laboratory Department of Mathematics and TheoriesPeng Cheng LaboratoryShenzhen 518000China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia

DURING our discussion at workshops for writing“What Does ChatGPT Say:The DAO from Algorithmic Intelligence to Linguistic Intelligence”[1],we had expected the next milestone for Artificial Intelligence(AI)would be in the direction of Imaginative Intelligence(II),i.e.,something similar to automatic wordsto-videos generation or intelligent digital movies/theater technology that could be used for conducting new“Artificiofactual Experiments”[2]to replace conventional“Counterfactual Experiments”in scientific research and technical development for both natural and social studies[2]-[6].Now we have OpenAI’s Sora,so soon,but this is not the final,actually far away,and it is just the beginning.

关键词： something Intelligence replace

来源：评论

学校读者我要写书评

暂无评论

The Fundamental Limitations of Learning Linear-Quadratic Regulators

The Fundamental Limitations of Learning Linear-Quadratic Reg...

引用

IEEE Conference on Decision and control

作者： Bruce D. Lee Ingvar Ziemann Anastasios Tsiamis Henrik Sandberg Nikolai Matni Department of Electrical and Systems Engineering University of Pennsylvania Automatic Control Laboratory ETH Zurich Division of Decision and Control Systems KTH Royal Institute of Technology

We present a local minimax lower bound on the excess cost of designing a linear-quadratic controller from offline data. The bound is valid for any offline exploration policy that consists of a stabilizing controller and an energy bounded exploratory input. The derivation leverages a relaxation of the minimax estimation problem to Bayesian estimation, and an application of van Trees inequality. We show that the bound aligns with system-theoretic intuition. In particular, we demonstrate that the lower bound increases when the optimal control objective value increases. We also show that the lower bound increases when the system is poorly excitable, as characterized by the spectrum of the controllability gramian of the system mapping the noise to the state and the $\mathcal{H}_{\infty}$ norm of the system mapping the input to the state. We further show that for some classes of systems, the lower bound may be exponential in the state dimension, demonstrating exponential sample complexity for learning the linear-quadratic regulator.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Data-driven modeling of heat pumps and thermal storage units for MPC

Data-driven modeling of heat pumps and thermal storage units...

引用

2023 International Conference on the Built Environment in Transition, CISBAT 2023

作者： Brandes, M. Cai, H. Vivian, J. Croci, L. Heer, P. Smith, R. Urban Energy Systems Laboratory Empa Dübendorf Switzerland Dept. of Industrial Engineering University of Padova Padua Italy Dept. of Power System Development Ricerca Sistema Energetico SpA Milan Italy Automatic Control Laboratory Department of Electrical Engineering and Information Technology ETH Zurich Switzerland

Heat pumps can play a crucial role in the European energy strategy 2050, which aims to achieve net-zero greenhouse gas emissions. When coupled with thermal energy storage and integrated with advanced control strategies, heat pump operation can be optimized to reduce carbon footprint and respond to the needs of system operators. However, to scale in a multitude of buildings, the transferability of the modeling into heterogeneous systems is crucial. In this paper, two different interpretable linear models, a hybrid (grey-box) and a fully data-driven (black-box) model are investigated. Specifically, two regression-based identification methods (SINDYc and DMDc) are used for dynamic models and the LASSO regression is used for static models. The transferability of the approach is evaluated using two real-world facilities with heterogeneous sizing and configuration. The results show a similar simulation performance for both cases with a maximum normalized RMSE of 0.41 and 0.60, respectively. This confirms the transferability of the approach that is necessary for large-scale implementation. © 2023 Institute of Physics Publishing. All rights reserved.

关键词： Carbon footprint

来源：评论

学校读者我要写书评

暂无评论

Out-of-distribution Object Detection through Bayesian Uncertainty Estimation

Out-of-distribution Object Detection through Bayesian Uncert...

引用

International Conference on Information Fusion

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

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.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Retinal disorder diagnosis based on hybrid deep learning models

引用

Multimedia Tools and Applications 2025年 1-25页

作者： Sedik, Ahmed El-Shafai, Walid El-Hag, Noha A. El-Banby, Ghada M. Abd El-Samie, Fathi E. Smart Systems Engineering Laboratory College of Engineering Prince Sultan University Riyadh11586 Saudi Arabia Department of the Robotics and Intelligent Machines Faculty of Artificial Intelligence Kafrelsheikh University Kafr el-Sheikh Egypt Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt The Higher Institute of Commercial Sciences Algarbia Al Mahalla Al Kubra31951 Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Anomaly detection from medical images is badly needed for automated diagnosis. For example, medical images obtained with several modalities, such as magnetic resonance (MR) and confocal microscopy, need to be classified for anomaly detection. The MR images may contain tumors that need to be detected with anomaly detection techniques. In MR imaging, brain tumors are represented as areas composed of abnormal cells that need to be detected. On the other hand, confocal microscopy can be used for retinal imaging. Hence, there is a need to apply classification techniques for diagnosing diseases of the eye, such as Diabetic Retinopathy (DR), which leads to exudates in different regions of the retina. The detection of exudates is necessary for the diagnosis of DR. In this paper, two models are presented for the classification of MR and retinal images. Much research has been done in this area, but it did not achieve high accuracy of classification in an acceptable time. In addition, the previous models did not consider both types of image modalities considered in this paper. The suggested models are Convolutional Neural Network (CNN) and Convolutional Long Short-Term Memory (Conv-LSTM). They are used to classify normal and abnormal cases of both brain tumor and DR diseases. The CNN model is composed of six convolutional layers and six max-pooling layers. A soft-max activation function takes the classification decision. The proposed Conv-LSTM model is composed of three stages: pre-processing, feature extraction, and classification. The deep learning model performance is better than those of traditional networks. The CNN gives an accuracy of 94.26% for DR classification and 95.8% for brain tumor classification, while the Conv-LSTM gives the maximum accuracy of 96.41% for DR classification and 97.4% for brain tumor classification. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Confocal microscopy

来源：评论

学校读者我要写书评

暂无评论

Keynote Talk: Qualitative model based diagnosis of complex systems using decomposition 22

Keynote Talk: Qualitative model based diagnosis of complex s...

引用

Proceedings of the 7th International Conference on Sustainable Information engineering and Technology

作者： Katalin M. Hangos Systems and Control Laboratory Institute for Computer Science and Control Hungary and Department of Electrical Engineering and Information Systems University of Pannonia Hungary

ISBN: (纸本)9781450397117

Decomposition offers the potential to reduce the complexity of model-based optimization, prediction, control and diagnosis by accounting for the structure and sparsity of the describing model. Motivated by this fact, a rich and powerful collection of decomposition methods are available for model based diagnosis of large-scale complex dynamic systems, too. At the same time, one usually does not have enough information about a large-scale complex dynamic system to construct its precise enough model, so a kind of qualitative dynamic model is often used for the diagnosis [1]. Two structural decomposition based qualitative diagnostic methods are presented in this lecture, together with their component-driven system decomposition ***, a model-based diagnostic method is described that is able to detect and isolate non-technical losses (illegal loads) in low voltage electrical grids of one transformer area [2]. As a preliminary off-line step of the diagnosis, a powerful electrical decomposition method is proposed, which breaks down the overall network to subsystems with one feeder layout enabling to make the necessary computations efficient. The diagnostic method is based on analyzing the differences between the measured and model-predicted voltages. The uncertainty in the model parameters together with the measurement uncertainties are also taken into account to make the approach applicable in real-world cases. The proposed method is able to detect and localize multiple illegal loads, and the amount of the illegal consumption can also be *** a second case study, a high level decomposition approach for process system fault diagnosis using event traces is given [3], [4]. Using a simple component graph model behind the process system and the measured trace applied for the diagnosis, the method can find the root cause(s) of propagating failures between separate components. The method can connect individually operating lower-level component-specific diag

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：