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arXiv 2021年

作者： Reed, Emily A. Ramos, Guilherme Bogdan, Paul Pequito, Sérgio Ming Hsieh Electrical and Computer Engineering Department University of Southern California United States Department of Electrical and Computer Engineering Faculty of Engineering University of Porto Portugal Delft University of Technology Delft Center for Systems and Control

Finding strongly connected components (SCCs) and the diameter of a directed network play a key role in a variety of discrete optimization problems, and subsequently, machine learning and control theory problems. On the one hand, SCCs are used in solving the 2-satisfiability problem, which has applications in clustering, scheduling, and visualization. On the other hand, the diameter has applications in network learning and discovery problems enabling efficient internet routing and searches, as well as identifying faults in the power grid. In this paper, we leverage consensus-based principles to find the SCCs in a scalable and distributed fashion with a computational complexity of O (Ddmax in-degree ) , where D is the (finite) diameter of the network and dmax in-degree is the maximum in-degree of the network. Additionally, we prove that our algorithm terminates in D + 1 iterations, which allows us to retrieve the diameter of the network. We illustrate the performance of our algorithm on several random networks, including Erdos-Rényi, Barabási- Albert, and Watts-Strogatz networks. Copyright © 2021, The Authors. All rights reserved.

关键词： Optimization

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A new source localization method using heteroscedasticity time series in passive sonar

A new source localization method using heteroscedasticity ti...

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OCEANS

作者： H. Amiri H. Amindavar M. Kamarei Control Research Department Engineering Research Institute Ministry of Agriculture Netherlands Department of Electrical Engineering Amirkabir University of Technology Spain Department of Electrical and Computer Engineering University of Tehran Iran

In this paper we propose a new source localization method using underwater ambient noise modeling based on heteroscedasticity time series in array signal processing for a passive SONAR. In this application, measurement of ambient noise in natural environment shows that noise can sometimes be significantly nonGaussian. Besides in many applications, such as those sensors having nonideal hardware, involving sparse hydrophones with prevailing external noise, the assumed noise model may be simplified by different sensors noise variances. Generalized Autoregressive Conditional Heteroscedasticity (GARCH) time series are feasible for heavy tailed probability density function (PDF) (as excess kurtosis) and time varying variances (a type of heteroscedasticity) of stochastic process. We use GARCH noise model in the Maximum Likelihood Approach for the estimation of Direction-Of-Arrivals (DOAs) of impinging sources. Through simulation, we show that the GARCH modeling is suitable for high-resolution source localization and noise suppression in an underwater environment.

关键词： Working environment noise Sonar measurements Array signal processing Noise measurement Hardware Sonar equipment Probability density function Stochastic processes Maximum likelihood estimation Direction of arrival estimation

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Frequency domain analysis of B-spline interpolation

Frequency domain analysis of B-spline interpolation

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Z. Mihajlovic A. Goluban M. Zagar Department of Electronics Microelectronics Computer and Intelligent Systems Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia Department of Control and Computer Engineering in Automation Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia

This paper describes B-spline interpolation and compares it with other reconstruction methods, especially in three-dimensional space. We first consider the B-spline bases in the terms of convolution in signal processing. The presented analysis requires careful usage of continuous and discrete representation of B-spline. Emphasis is given to the important difference between B-spline interpolation and approximation. The difference is shown through frequency domain analysis, so we derive frequency responses of the B-spline interpolation and approximation. We conclude by demonstrating the use of several reconstruction filters and appropriate gradient estimators in volume rendering. Exact reconstruction in volume visualization is very important in many industrial applications, such as material cavity control.

关键词： Frequency domain analysis Spline Interpolation Image reconstruction Convolution Filters Polynomials Data visualization Frequency response Microelectronics

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Vision-based nighttime vehicle detection and range estimation for driver assistance

Vision-based nighttime vehicle detection and range estimatio...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Yen-Lin Chen Chuan-Tsai Lin Chung-Jui Fan Chih-Ming Hsieh Bing-Fei Wu Department of Computer Science and Information Engineering Asia University Taichung Taiwan Department of Electrical and Control Engineering National Chiao Tung University Hsinchu Taiwan

This paper presents a real-time vision system for assisting driver during nighttime driving. The proposed system provides the following features: 1) effectively detection and tracking of oncoming and preceding vehicles based on image segmentation and pattern analysis techniques. 2) Robust and adaptive vehicle detection under various illuminated conditions at nighttime urban environments benefited by a novel automatic object segmentation scheme. 3) Providing beneficial information for assisting the driver to perceive surrounding traffic conditions outside the car during nighttime driving. 4) Providing a versatile control strategy for in-vehicle facilities of the autonomous vehicles. 5) Offering real-time traffic event-driven video surveillance machinery for recording evidences of possible traffic accidents. Experimental results demonstrate the feasibility and effectiveness of the proposed system on nighttime driver assistance issues.

关键词： Vehicle detection Real time systems Vehicle driving Mobile robots Machine vision computer vision Object detection Image segmentation Pattern analysis Robust control

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Adaptive neural state-feedback stabilizing controller for nonlinear systems with mismatched uncertainty

Adaptive neural state-feedback stabilizing controller for no...

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World Congress on Intelligent control and Automation (WCICA)

作者： Mohammad M. Arefi Mohammad R. Jahed-Motlagh Hamid R. Karimi Department of Power and Control Engineering Shiraz University Shiraz Iran Computer Engineering Department Iran University of Science and Technology Tehran Iran Department of Engineering University of Agder Grimstad Norway

In this paper, an adaptive neural network (NN) state-feedback controller for a class of nonlinear systems with mismatched uncertainties is presented. By using a radial basis (RBF) neural network, a bound of unknown nonlinear functions is approximated so that no information about the upper bound of mismatched uncertainties is required. The state-feedback is based on Lyapunov stability theory, and it is shown that the asymptotic convergence of the closed-loop system to zero is achieved while maintaining bounded states at the same time. The presented methods are more general than the previous approaches, handling systems with no restriction on the dimension of the system and the number of inputs. Simulation results on dynamic equations of vertical take-off and landing (VTOL) helicopter confirm the effectiveness of the proposed methods in the stabilization of mismatched nonlinear systems.

关键词： Uncertainty Artificial neural networks Approximation methods Vectors Adaptive systems Nonlinear systems

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Robust exponential stabilization for a class of nonlinear dynamical systems with unmatched uncertainties

Robust exponential stabilization for a class of nonlinear dy...

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IEEE Conference on control Technology and Applications (CCTA)

作者： Kai Yu Chang-An Zhao Guang-Ren Duan Department of Control Science and Engineering Harbin Institute of Technology Harbin People's Republic of China Department Electrical and Computer Engineering Northeastern University USA

In this paper, the problem of robust exponential stabilization for a class of nonlinear dynamical systems with unmatched uncertainties is investigated. Based on the stability of the nominal system, a new approach to synthesizing a class of continuous state feedback controllers for uncertain nonlinear dynamical systems is proposed. By such a class of feedback controller, we can guarantee exponential stability of uncertain nonlinear dynamical systems. Our approach gives a clear insight into system analysis. Finally, an illustrative example is given to demonstrate the utilization of the approach developed.

关键词： Robustness Nonlinear dynamical systems Uncertainty Stability control system synthesis State feedback control systems Nonlinear control systems Adaptive control Mathematical model

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Robust learning via ensemble density propagation in deep neural networks

arXiv

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arXiv 2021年

作者： Carannante, Giuseppina Dera, Dimah Rasool, Ghulam Bouaynaya, Nidhal C. Mihaylova, Lyudmila Rowan University Department of Electrical and Computer Engineering GlassboroNJ United States University of Sheffield Department of Automatic Control and Systems Engineering United Kingdom

Learning in uncertain, noisy, or adversarial environments is a challenging task for deep neural networks (DNNs). We propose a new theoretically grounded and efficient approach for robust learning that builds upon Bayesian estimation and Variational Inference. We formulate the problem of density propagation through layers of a DNN and solve it using an Ensemble Density Propagation (EnDP) scheme. The EnDP approach allows us to propagate moments of the variational probability distribution across the layers of a Bayesian DNN, enabling the estimation of the mean and covariance of the predictive distribution at the output of the model. Our experiments using MNIST and CIFAR-10 datasets show a significant improvement in the robustness of the trained models to random noise and adversarial attacks. © 2021, CC BY.

关键词： Deep neural networks

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An AI-Driven Framework for Personalized Diet Generation and Nutrition Suggestions Using Machine Learning, computer Vision and NLP

An AI-Driven Framework for Personalized Diet Generation and ...

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Integrated Intelligence and Communication Systems (ICIICS), International Conference on

作者： Jyoti Kanjalkar Pramod Kanjalkar Raj Khanke Rushikesh Mane Kunal Kharat Kanad Kolhe Department of Computer Science & Engineering (AIML) Vishwakarma Institute of Technology Pune India Department of Instrumentation & Control Engineering Vishwakarma Institute of Technology Pune India

ISBN: (数字)9798331504960

ISBN: (纸本)9798331504977

To counteract unhealthy eating habits among the younger generation, a novel and economical AI-powered framework has been developed to serve as a virtual nutritionist and nutrition counsellor. The system uses machine learning, computer vision, and natural language processing to provide personalized nutrition plans via an easy-to-use online application. It generates tailored meal plans that consider user preferences, allergies, and meal times by calculating Body Mass Index (BMI) based on user input. In addition to blog links and tailored training regimens (enhanced by the LLM3 model trained on a Kaggle gym dataset), a feedback mechanism allows for continuous optimization. Real-time food classification uses VGG16 and ResNet deep learning models to detect damaged or harmful foods and send out alerts for unsuitable foods. Additionally, integration with Google Maps and KNN helps users locate nearby dietitians, fostering better access to professional guidance. These comprehensive improvements significantly contribute to maintaining a good diet.

关键词： Photography computer vision Wearable Health Monitoring Systems Visualization Web services Real-time systems Natural language processing User experience Satellite images Allergies

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Design of separating screen for tenebrio molitor L

Design of separating screen for tenebrio molitor L

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International Conference on Vehicle and Mechanical engineering and Information Technology, VMEIT 2014

作者： Wang, Li Ping Guo, Yi Fu, Gang Dong, Jiang Hui College of Mechanical and Electronic Engineering Shanghai Jianqiao University Shanghai 201319 China School of Computer Science Engineering and Mathematics Flinders University SA 5042 Australia Beijing Vocational College of Agriculture Beijing 102442 China China Satellite Maritime Tracking and Control Department Jiangyin 214431 China

ISBN: (纸本)9783038350606

In order to meet requirement of separation screen for tenebrio molitor L, one separation screen was designed, this product has a good separation, simple structure, low cost, high efficiency, easy operation. Based on the analysis of design requirement of separating screen for tenebrio molitor L, overall structure, working principle and the main structural parameters were determined. The kinematic mathematical model of shaking mechanism was established by using the vector method. The kinematics analysis of shaking mechanism was conducted by using Matlab, the displacement, velocity and acceleration curves of sieve box were obtained. The performance test showed that the prototype machine can screen different instar tenebrio molitor L and frass, this machine has good screening effect. In addition, machine design and performance are able to meet the design requirements. © (2014) Trans Tech Publications, Switzerland.

关键词： Machine design

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Some Remarks on the Issue of Second-order Optimality Conditions in control Problems with Mixed Constraints

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IFAC-PapersOnLine 2022年第16期55卷 231-235页

作者： Aram V. Arutyunov Dmitry Yu. Karamzin Fernando Lobo Pereira V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences Moscow Federal Research Center “Computer Science and Control” of Russian Academy of Sciences Electrical Engineering Department of Engineering Faculty University of Porto Portugal

A smooth optimal control problem with mixed constraints is considered. Under the normality assumption, a proof of second-order necessary optimality conditions based on the Robinson stability theorem is provided. The main feature of the obtained result is that the local regularity with respect to the mixed constraints is assumed, that is, a regularity in an ε-tube along the minimizer, but not the conventional global regularity hypothesis. This impacts the maximum condition. Therefore, the normal set of Lagrange multipliers fulfills the Legendre-Clebsch condition and the maximum principle. At the same time, the maximum condition is modified since, now, the maximum is taken over a reduced feasible set. Furthermore, the case of abnormal minimizers is considered. The same type of reduced maximum condition is obtained along with a refined Legendre-Clebsch condition which is meaningful in the abnormal case.

关键词： Optimal control Nonlinear control Maximum principle Mixed constraints Normal abnormal minimizers

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