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A Convergence Criterion of Newton’s Method Based on the Heisenberg Uncertainty Principle

International Journal of Applied and Computational Mathematics 2022年第1期8卷 1-8页

作者： Kouhkani, S. Koppelaar, H. Taghipour Birgani, O. Argyros, I.K. Radenović, S. Department of Mathematics Islamic Azad University branch of Shabestar Shabestar Iran Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft Netherlands Department of Mathematics Iran University of Science and Technology Tehran Iran Department of Mathematical Sciences Cameron University Lawton 73505 OK United States Faculty of Mechanical Engineering University of Belgrade Belgrade Serbia

The objective in this article is to extend the applicability of Newton’s method for solving Banach space valued nonlinear equations. In particular, a new semi-local convergence criterion for Newton’s method (NM) based on Kantorovich theorem in Banach space is developed by application of the Heisenberg Uncertainty Principle (HUP). The convergence region given by this theorem is small in general limiting the applicability of NM. But, using HUP and the Fourier transform of the operator involved, we show that it is possible to extend the applicability of NM without additional hypotheses. This is done by enlarging the convergence region of NM and using the concept of epsilon-concentrated operator. Numerical experiments further validate our theoretical results by solving equations in case not covered before by the Newton–Kantorovich theorem. © 2022, The Author(s), under exclusive licence to Springer Nature India Private Limited.

关键词： Banach space Heisenberg uncertainty principle Iterative method Kantorovich theorem Newton’s method

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A Design and Implementation of M Tyoe Systems wnhcih uses ICT Technology in Grids

A Design and Implementation of M Tyoe Systems wnhcih uses IC...

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International Conference on Power Energy, Environment and Intelligent control (PEEIC)

作者： Satish Kumar Jangid Alka Singh V. Pushparajesh Department of Electrical Engineering Vivekananda Global University Jaipur India Master of Computer Application Noida Institute of Engineering & Technology Greater Noida Uttar Pradesh India Department of Electrical and Elceltronics Engineeirng Faculty of Engineering and Technology JAIN (Deemed to be University) Bangalore India

In the context of smart grids, multi-agent-based applications have garnered a lot of interest recently. Concurrently, integration of IT (information and communication technology) has emerged as a crucial element of the infrastructure of smart grids. This research attempts to give a comprehensive assessment of the technological framework and literature pertaining to the utilization of Multi-Agent Societies (MAS) and the addition of information and communication technologies in electrical power system deployments. In the environment of artificially intelligent grids, agents are thought of as sentient beings that can make decisions and behave in a dynamic and autonomous way by drawing on their innate intellect and past experiences. ICT also makes data and information transmission easier, which is a game-changer in the transition from conventional to smart grids. This article summarizes the multi-agent concept in smart grids and offers a thorough literature study on related topics to elucidate their applications. Additionally, it pays particular attention to Cti standards, particularly IEC 61850, which integrates MAS with ICT. The last section of the paper introduces laboratory framework concepts, which provide insight on the actual use of IEC 61850.

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A Novel Approach for Implementing LFSRs Using QCA Technology

A Novel Approach for Implementing LFSRs Using QCA Technology

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International Conference on Vision Towards Emerging Trends in Communication and Networking (ViTECoN)

作者： C. Manikandan C. Veda Vardhan L. Sai Rishitha K. Saranya A Rajesh R. Amirtharajan Thanikaiselvan Veeramalai Hemalatha Mahalingam Faculty School of Electrical & Electronics Engineering SASTRA Deemed University Thanjavur Tamil Nadu India School of Electronics Engineering Vellore Institute of Technology Vellore India Department of Electrical and Computer Engineering King Abdulaziz University Jeddah Saudi Arabia

Quantum random number generators have attracted the research community for providing secure communication. This paper presents a novel Quantum LFSR, designed using the novel construction of D-Flip-Flop (DFF) and XOR gates in QCA. The suggested Quantum LFSR comprises 216 cells with an area of 0.23μm2 and the total power dissipation is 0.31442 eV, 0.41729 eV, and 0.54389 eVat different standard tunnelling energy levels. The power parameters are analysed using QCA Pro, and the calculated outcomes show that the Quantum LFSR has low power consumption and reduced footprint compared to conventional designs.

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Hidden Multidimensional Modulation Side Channels in Quantum Protocols

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Physical Review Letters 2025年第13期134卷 130802-130802页

作者： Amita Gnanapandithan Li Qian Hoi-Kwong Lo Department of Electrical and Computer Engineering University of Toronto Toronto Canada Center for Quantum Information and Quantum Control University of Toronto Toronto Canada Quantum Bridge Technologies Inc. 108 College Street Toronto Canada

Quantum protocols including quantum key distribution and blind quantum computing often require the preparation of quantum states of known dimensions. Here, we show that, rather surprisingly, hidden multidimensional modulation is often performed by practical devices. This violates the dimensional assumption in quantum protocols, thus creating side channels and security loopholes. Our work has important impacts on the security of quantum cryptographic protocols.

关键词： Quantum cryptography

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A Data-Driven Distributed control Scheme: Learning Multi-Objective Agent-Based MPC for Path-Tracking

A Data-Driven Distributed Control Scheme: Learning Multi-Obj...

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International Conference on Intelligent Transportation

作者： Jiaming Zhong Reza Valiollahi Mehrizi Yash Vardhan Pant Amir Khajepour Department of Mechanical and Mechatronics Engineering Mechatronic Vehicle Systems (MVS) Lab University of Waterloo Waterloo ON Canada Department of Electrical and Computer Engineering Control Learning and Logic (CL2) group University of Waterloo Waterloo ON Canada

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

Agent-based model predictive control (AMPC) has recently been proposed for vehicle systems with various controllers, such as differential braking and torque vectoring, where controllers are regarded as distributed agents contributing to the same objective. However, this scheme is challenging in handling multiple conflicting objectives with coupled agents. A common approach for such tasks is the integrated MPC, where all objectives and agents are stacked together in one optimization. Nevertheless, as more agents and objectives are involved, the integrated MPC will face challenges like computational burdens and maintenance difficulties in practice. To this end, this paper proposes a learning multi-objective AMPC that can improve design flexibility and computing efficiency. First, under the assumption of information exchange, a multi-objective AMPC tailored from the alternating direction method of multipliers (ADMM) is proposed to decouple the system and achieve the same performance as the integrated scheme iteratively. Second, a learning-based method for initializing iterations is proposed to accelerate convergence. In addition, a data management method is proposed for real-time efficiency, and an authentication module is designed for learning reliability. We compare the proposed scheme against the integrated scheme via a combined path-tracking simulation for autonomous vehicles with various controllers. The proposed scheme achieves the same control performance as the integrated one while reducing the computational time by 43.5 %. Furthermore, the learning-based method saves 88.6% more computational time than without learning, making it suitable for real-time implementation.

关键词： Learning systems Torque Decentralized control Reliability engineering Real-time systems Convex functions Planning Information exchange Convergence Predictive control

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Three Dimensional Moving Path following control for Robotic Vehicles with Minimum Positive Forward Speed

Three Dimensional Moving Path following Control for Robotic ...

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2021 American control Conference, ACC 2021

作者： Jain, R. Praveen De Sousa, Joao Borges Aguiar, A. Pedro Norwegian University of Science and Technology Department of Engineering Cybernetics Trondheim7491 Norway University of Porto Faculty of Engineering Department of Electrical and Computer Engineering Porto4200-465 Portugal

ISBN: (纸本)9781665441971

This paper addresses the problem of steering a robotic vehicle along a geometric path specified with respect to a reference frame moving in three dimensions, termed the Moving Path Following (MPF) motion control problem. The MPF problem is solved for a large class of robotic vehicles that require a minimum positive forward speed to operate. This restriction poses additional challenges with respect to the control design, and is developed using geometric concepts, wherein the attitude control problem is formulated on the Special Orthogonal group SO(3). To this end, a MPF error model formulation is first derived that allows to exclude the conservative constraints on the initial position of the vehicle with respect to the reference path by enabling the explicit control of the progression of a virtual point moving along the reference path. The task of the MPF control law is then to steer the vehicle towards the moving path and to converge to the virtual point. Stability and convergence guarantees of the resulting closed-loop system are provided using the Input-to-State Stability concept. In particular, we show that the proposed controller is robust to imperfect tracking errors by the autopilot and wind gusts. Simulation results are presented to illustrate the efficacy of the proposed MPF control law. © 2021 American Automatic control Council.

关键词： Attitude control

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Congestion Aware Genetic Q-learning Based RPL Routing Protocol for Vehicle Ad-Hoc Networks 5

Congestion Aware Genetic Q-learning Based RPL Routing Protoc...

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5th International Conference on engineering Technology and its Applications, IICETA 2022

作者： Rashid, Sami Abduljabbar Habelalmateen, Mohammed I. Ahmed, Ahmed Jamal Abbas, Ali Hashim Jubair, Mohammed Ahmed Hassan, Mustafa Hamid Abdulhadi, Ahmed Hammed, Shimah Audah, L. Al-Maarif University College Department of Computer Engineering Techniques Al-Anbar Iraq Islamic University College of Technical Engineering Department of Computer Technical Engineering Najaf54001 Iraq Imam ja'Afar Al-Sadiq University College of Information Technology Department of Computer Technical Engineering Al-Muthanna 66002 Iraq Al-Farahidi University Engineering Technical College Baghdad Iraq Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia Batu Pahat Malaysia

ISBN: (纸本)9781665472159

Vehicular Ad-Hoc Network (VANET) is the one among the prominent research area. On behalf of its eminent behaviour link dynamically varying topology, huge mobility, irregular connectivity and density it is still in the open research area. Its dynamic nature is the biggest challenge to do data transmission among the network. This research work introduced a novel protocol which is Congestion Aware Genetic Q-Learning (CAGQ) based RPL routing protocol for VANET networks. The major sub sections of the protocol are system model, mobility model, and preeminent path selection and trickle timer based genetic Q-Learning. The extensive evaluation is done through simulation which analysed the performance of RPL routing protocol in extremely dynamic vehicular environment. The contiki based Cooja simulator is employed for the process of simulation. The calculated results of the protocol CAGQ model is compared with the earlier works such as MRHOFL and EMCC. The analysis is done by calculating the parameters such as packet delivery ratio and Routing overhead. This result indicates that the proposed CAGQ method performed better and produced good results in data transmission even in huge mobility based VANETs. © 2022 IEEE.

关键词： Genetic algorithms

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Nonlinear MPC for Full-Pose Manipulation of a Cable-Suspended Load using Multiple UAVs

Nonlinear MPC for Full-Pose Manipulation of a Cable-Suspende...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Sihao Sun Antonio Franchi Robotics and Mechatronics Department Electrical Engineering Mathematics and Computer Science (EEMCS) Faculty University of Twente AE Enschede The Netherlands Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy LAAS-CNRS Université de Toulouse Toulouse France

In this work, we propose a centralized control method based on nonlinear model predictive control to let multiple UAVs manipulate the full pose of an object via cables. At the best of the authors knowledge this is the first method that takes into account the full nonlinear model of the load-UAV system, and ensures all the feasibility constraints concerning the UAV maximumum and minimum thrusts, the collision avoidance between the UAVs, cables and load, and the tautness and maximum tension of the cables. By taking into account the above factors, the proposed control algorithm can fully exploit the performance of UAVs and facilitate the speed of operation. Simulations are conducted to validate the algorithm to achieve fast and safe manipulation of the pose of a rigid-body payload using multiple UAVs. We demonstrate that the computational time of the proposed method is sufficiently small (<100 ms) for UAV teams composed by up to 10 units, which makes it suitable for a huge variety of future industrial applications, such as autonomous building construction and heavy-load transportation.

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Temporal Feature Matters: A Framework for Diffusion Model Quantization

arXiv

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arXiv 2024年

作者： Huang, Yushi Gong, Ruihao Liu, Xianglong Liu, Jing Li, Yuhang Lu, Jiwen Tao, Dacheng Electrical and Computer Engineering Department Hong Kong University of Science and Technology Hong Kong State Key Laboratory of Software Development Environment Beihang University China Department of Data Science and AI Faculty of IT Monash University Australia Electrical Engineering Department Yale University United States Department of Automation Tsinghua University China School of Computer Science and Engineering Nanyang Technological University Singapore

The Diffusion models, widely used for image generation, face significant challenges related to their broad applicability due to prolonged inference times and high memory demands. Efficient Post-Training Quantization (PTQ) is crucial to address these issues. However, unlike traditional models, diffusion models critically rely on the time-step for the multi-round denoising. Typically, each time-step is encoded into a hypersensitive temporal feature by several modules. Despite this, existing PTQ methods do not optimize these modules individually. Instead, they employ unsuitable reconstruction objectives and complex calibration methods, leading to significant disturbances in the temporal feature and denoising trajectory, as well as reduced compression efficiency. To address these challenges, we introduce a novel quantization framework that includes three strategies: 1) TIB-based Maintenance: Based on our innovative Temporal Information Block (TIB) definition, Temporal Information-aware Reconstruction (TIAR) and Finite Set Calibration (FSC) are developed to efficiently align original temporal features. 2) Cache-based Maintenance: Instead of indirect and complex optimization for the related modules, pre-computing and caching quantized counterparts of temporal features are developed to minimize errors. 3) Disturbance-aware Selection: Employ temporal feature errors to guide a fine-grained selection between the two maintenance strategies for further disturbance reduction. This framework preserves most of the temporal information and ensures high-quality end-to-end generation. Extensive testing on various datasets, diffusion models and hardware confirms our superior performance and acceleration. © 2024, CC BY.

关键词： Spatio-temporal data

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Simultaneous distributed estimation and attack detection/isolation in social networks: Structural observability, kronecker-product network, and chi-square detector

Simultaneous distributed estimation and attack detection/iso...

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2021 IEEE International Conference on Autonomous Systems, ICAS 2021

作者： Doostmohammadiany, Mohammadreza Charalambous, Themistoklis Shafie-Khah, Miadreza Meskin, Nader Khan, Usman A. Aalto University School of Electrical Engineering Espoo Finland Faculty of Mechanical Engineering Semnan University Semnan Iran School of Technology and Innovations University of Vaasa Vaasa Finland Qatar University Electrical Engineering Department Doha Qatar Tufts University Electrical and Computer Engineering Department MedfordMA United States

ISBN: (纸本)9781728172897

This paper considers distributed estimation of linear systems when the state observations are corrupted with Gaussian noise of unbounded support and under possible random adversarial attacks. We consider sensors equipped with single time-scale estimators and local chi-square $(\chi^{2})$ detectors to simultaneously observe the states, share information, fuse the noise/attack-corrupted data locally, and detect possible anomalies in their own observations. While this scheme is applicable to a wide variety of systems associated with full-rank (invertible) matrices, we discuss it within the context of distributed inference in social networks. The proposed technique outperforms existing results in the sense that: (i) we consider Gaussian noise with no simplifying upper-bound assumption on the support;(ii) all existing $\chi^{2}$-based techniques are centralized while our proposed technique is distributed, where the sensors locally detect attacks, with no central coordinator, using specific probabilistic thresholds;and (iii) no local-observability assumption at a sensor is made, which makes our method feasible for large-scale social networks. Moreover, we consider a Linear Matrix Inequalities (LMI) approach to design block-diagonal gain (estimator) matrices under appropriate constraints for isolating the attacks. © 2021 IEEE.

关键词： Observability

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