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arXiv 2022年

作者： Liu, Yuting Lee, Albert Qian, Kun Zhang, Peng He, Haoran Ren, Zheyu Cheung, Shun Kong Li, Yaoyin Zhang, Xu Ma, Zichao Xiao, Zhihua Yu, Guoqiang Wang, Xin Liu, Junwei Wang, Zhongrui Wang, Kang L. Shao, Qiming Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Clear Water Bay Kowloon 999077 Hong Kong School of Material Science and Engineering Harbin Institute of Technology Shenzhen518055 China Device Research Laboratory Department of Electrical and Computer Engineering University of California Los AngelesCA90095 United States IAS Center for Quantum Technologies The Hong Kong University of Science and Technology Hong Kong Department of Electrical and Electronic Engineering The University of Hong Kong Pokfulam Road 999077 Hong Kong Department of Physics The Hong Kong University of Science and Technology Clear Water Bay Kowloon 999077 Hong Kong Beijing National Laboratory for Condensed Matter Physics Institute of Physics University of Chinese Academy of Sciences Chinese Academy of Sciences Beijing100190 China Department of Physics The City University of Hong Kong 999077 Hong Kong Guangdong-Hong Kong-Macao Joint Laboratory for Intelligent Micro-Nano Optoelectronic Technology The Hong Kong University of Science and Technology Hong Kong ACCESS AI Chip Center for Emerging Smart Systems InnoHK Centers Hong Kong Science Park Hong Kong

Cryogenic electronics have become essential in reducing the number of input/output ports to the quantum chips and generating multiplexed reading and control pulses for scalable quantum computation 1-5. A demanding request for cryogenic electronics is to support efficient machine learning algorithms, which have been proven effective for essential quantum computation tasks such as quantum error correction and quantum control 6,7. However, current digital cryogenic electronics suffer from the von Neumann bottleneck, where the physical separation of computation and memory units causes a huge amount of energy and delay when processing data-intensive programs. Energy-efficient hardware implementation of machine learning algorithms for quantum computation requires nonvolatile and electrically-programmable devices, memristors, working at cryogenic temperatures that enable in-memory computing 8,9. Magnetic topological insulators are promising candidates due to their tunable magnetic order by electrical currents with high energy efficiency 10-15. Here, we utilize magnetic topological insulators as memristors (termed magnetic topological memristors) and introduce a chiral edge state-based cryogenic in-memory computing scheme. On the one hand, the chiral edge state can be tuned from left-handed to right-handed chirality through spin-momentum locked topological surface current injection. On the other hand, the chiral edge state exhibits giant and bipolar anomalous Hall resistance, which facilitates the electrical readout. The memristive switching and reading of the chiral edge state exhibit high energy efficiency, high stability, and low stochasticity. We achieve high accuracy in a proof-of-concept classification task using four magnetic topological memristors. Furthermore, our algorithm-level and circuit-level simulations of large-scale neural networks based on magnetic topological memristors demonstrate a software-level accuracy and lower energy consumption for image recogniti

关键词： Topology

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State estimation for a class of linear systems with quadratic output

arXiv

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arXiv 2020年

作者： Theodosis, Dionysios Berkane, Soulaimane Dimarogonas, Dimos V. Dynamic Systems and Simulation Laboratory School of Production Engineering and Management Technical University of Crete Greece Département d’informatique et d’ingénierie Université du Québec en Outaouis GatineauQC Canada Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden

This paper deals with the problem of state estimation for a class of linear time-invariant systems with quadratic output measurements. An immersion-type approach is presented that transforms the system into a state-affine system by adding a finite number of states to the original system. Under suitable persistence of excitation conditions on the input and its higher derivatives, global state estimation is exhibited by means of a Kalman-type observer. A numerical example is provided to illustrate the applicability of the proposed observer design for the problem of position and velocity estimation for a vehicle navigating in the n−dimensional Euclidean space using a single position range measurement. Copyright © 2020, The Authors. All rights reserved.

关键词： State estimation

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Dynamic analysis of high-dimensional fractional-order gene regulation networks with time delay

Dynamic analysis of high-dimensional fractional-order gene r...

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Chinese control Conference (CCC)

作者： Zhe Zhang Can Ding Jing Zhang Feng Liu Yingjie Zhang Fanyong Cheng College of Electrical and Information Engineering Hunan University Changsha China School of Automation China University of Geosciences Wuhan China College of Computer Science and Electronic Engineering Hunan University Changsha China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fujian China

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

This paper mainly analyzes the stability of high-dimensional fractional-order gene regulatory network systems with time delay. Based on the judgment of eigenvalues, this paper proposes sufficient information about the stability of high-dimensional fractional-order gene regulatory network systems with time delay. Conditions, and by analyzing the characteristic equations, the bifurcation conditions of the high-dimensional fractional-order gene regulatory network system with time delay are derived. Finally, the theoretical part of this paper is verified by numerical simulation.

关键词： Bifurcation Timing Stability analysis Mathematical model Delay effects Numerical stability Electronic mail

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Dendrite Net with Acceleration Module for Faster Nonlinear Mapping and System Identification

arXiv

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arXiv 2020年

作者： Liu, Gang Pang, Yajing Yin, Shuai Niu, Xiaoke Wang, Jing Wan, Hong School of Electrical and Information Engineering Zhengzhou University Zhengzhou450001 China Institute of Robotics and Intelligent Systems Xi'an Jiaotong University Xi'An710049 China Henan Provincial Key Laboratory of Brain Science and Brain-Computer Interface Technology Zhengzhou450001 China

Nonlinear mapping is an essential and common demand in online systems, such as sensor systems and mobile phones. Accelerating nonlinear mapping will directly speed up online systems. Previously the authors of this paper proposed a Dendrite Net (DD) with enormously lower time complexity than the existing nonlinear mapping algorithms;however, there still are redundant calculations in DD. This paper presents a DD with an acceleration module (AC) to accelerate nonlinear mapping further. We conduct three experiments to verify whether DD with AC has lower time complexity while retaining DD's nonlinear mapping properties and system identification properties: The first experiment is the precision and identification of unary nonlinear mapping, reflecting the calculation performance using DD with AC for basic functions in online systems. The second experiment is the mapping precision and identification of the multi-input nonlinear system, reflecting the performance for designing online systems via DD with AC. Finally, this paper compares the time complexity of DD and DD with AC and analyzes the theoretical reasons through repeated experiments. Results: DD with AC retains DD's excellent mapping and identification properties and has lower time complexity. Significance: DD with AC can be used for most engineering systems, such as sensor systems, and will speed up computation in these online systems. The code of DD with AC is available on GitHub:Gang neuron. © 2020, CC BY-NC-SA.

关键词： Online systems

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Periodic event-triggered output regulation for linear multi-agent systems

arXiv

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arXiv 2020年

作者： Zheng, Shiqi Shi, Peng Agarwal, Ramesh K. Lim, Chee Peng School of Automation China University of Geosciences Wuhan430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China School of Electrical and Electronic Engineering University of Adelaide AdelaideSA5005 Australia Department of Mechanical Engineering Washington University Box 1185 St Louis CampusMO63130 United States Institute for Intelligent Systems Research and Innovation Deakin University Australia

This study considers the problem of periodic event-triggered (PET) cooperative output regulation for a class of linear multi-agent systems. The advantage of the PET output regulation is that the data transmission and triggered condition are only needed to be monitored at discrete sampling instants. It is assumed that only a small number of agents can have access to the system matrix and states of the leader. Meanwhile, the PET mechanism is considered not only in the communication between various agents, but also in the sensorto-controller and controller-to-actuator transmission channels for each agent. The above problem set-up will bring some challenges to the controller design and stability analysis. Based on a novel PET distributed observer, a PET dynamic output feedback control method is developed for each follower. Compared with the existing works, our method can naturally exclude the Zeno behavior, and the inter-event time becomes multiples of the sampling period. Furthermore, for every follower, the minimum inter-event time can be determined a prior, and computed directly without the knowledge of the leader information. An example is given to verify and illustrate the effectiveness of the new design scheme. Copyright © 2020, The Authors. All rights reserved.

关键词： Multi agent systems

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Optimize Student Learning via Random Forest-Based Adaptive Narrative Game

Optimize Student Learning via Random Forest-Based Adaptive N...

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IEEE International Conference on Automation Science and engineering (CASE)

作者： Ryan Hare Ying Tang Wei Cui Joleen Liang Department of Electrical and Computer Engineering Rowan University Glassboro USA State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Institute of Smart Education Qingdao Academy of Intelligent Industries Qingdao China Squirrel AI Learning Shanghai China

ISBN: (数字)9781728169040

ISBN: (纸本)9781728169057

This paper presents an adaptive narrative game system that focuses on sequential logic design. The system adapts a random forest machine learning model to estimate a student's current level of domain knowledge relative to the problem presented to him through his game-playing behavior data, such as time taken to find solutions, errors in solutions, and emotional indicators. Hints, prompts, and/or individualized lessons are then offered to the player to guide their learning in a positive and productive direction. Our preliminary pilot study demonstrates that the model can make accurate classifications, from which proper assistance can then be provided to individual students as they play.

关键词： Games Databases Forestry Education Problem-solving Presses Artificial intelligence

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Correction to: SleepBoost: a multi‑level tree‑based ensemble model for automatic sleep stage classification

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Medical & biological engineering & computing 2024年第9期62卷 2785页

作者： Akib Zaman Shiu Kumar Swakkhar Shatabda Iman Dehzangi Alok Sharma Computer Science and Artificial Intelligence Laboratory (CSAIL) Electrical Engineering and Computer Science Department Massachusetts Institute of Technology Cambridge MA USA. School of Electrical & Electronics Engineering Fiji National University Suva Fiji. shiu.kumar@fnu.ac.fj. Centre for Artificial Intelligence and Robotics (CAIR) United International University Dhaka Bangladesh. Department of Computer Science Rutgers University Camden NJ USA. Center for Computational and Integrative Biology Rutgers University Camden USA. Laboratory for Medical Science Mathematics RIKEN Center for Integrative Medical Sciences Yokohama 230‑0045 Japan. Institute for Integrated and Intelligent Systems Griffith University Nathan Brisbane QLD Australia.

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A Piecewise-Markovian Lyapunov Approach to Reliable Output Feedback control for Fuzzy-Affine systems With Time-Delays and Actuator Faults

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IEEE TRANSACTIONS ON CYBERNETICS 2018年第9期48卷 2723-2735页

作者： Wei, Yanling Qiu, Jianbin Shi, Peng Wu, Ligang State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China School of Electrical and Electronic Engineering University of Adelaide Adelaide SA Australia Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin China

This paper addresses the problem of delay-dependent robust and reliable H-infinity static output feedback (SOF) control for a class of uncertain discrete-time Takagi-Sugeno fuzzy-affine (FA) systems with time-varying delay and actuator faults in a singular system framework. The Markov chain is employed to describe the actuator faults behaviors. In particular, by utilizing a system augmentation approach, the conventional closed-loop system is converted into a singular FA system. By constructing a piecewise-Markovian Lyapunov-Krasovskii functional, a new H-infinity performance analysis criterion is then presented, where a novel summation inequality and S-procedure are succeedingly employed. Subsequently, thanks to the special structure of the singular system formulation, the piecewise-affine SOF controller design is proposed via a convex program. Lastly, illustrative examples are given to show the efficacy and less conservatism of the presented approach.

关键词： Piecewise Markovian Lyapunov functional reliable output feedback control time-varying delay T-S fuzzy-affine (FA) systems

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A Primal-Dual SGD Algorithm for Distributed Nonconvex Optimization

arXiv

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arXiv 2020年

作者： Yi, Xinlei Zhang, Shengjun Yang, Tao Chai, Tianyou Johansson, Karl H. The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden The Department of Electrical Engineering University of North Texas DentonTX76203 United States The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China

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 considered. This problem is an important component of many machine learning techniques with data parallelism, such as deep learning and federated learning. We propose a distributed primal–dual stochastic gradient descent (SGD) algorithm, suitable for arbitrarily connected communication networks and any smooth (possibly nonconvex) cost functions. We 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 iterations. We also show that the output of the proposed algorithm with constant parameters linearly converges to a neighborhood of a global optimum. We demonstrate through numerical experiments the efficiency of our algorithm in comparison with the baseline centralized SGD and recently proposed distributed SGD algorithms. Copyright © 2020, The Authors. All rights reserved.

关键词： Cost functions

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Fuzzy Rate Analysis of Operators and its Applications in Linear Spaces

Research Square

引用

Research Square 2021年

作者： Zhang, Yijin Li, Honggang Jin, Maoming Lin, Zongbing Nanjing Changjiang Waterway Engineering Bureau China Key Lab of Intelligent Analysis and Decision on Complex Systems Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China Pass College Chongqing Technology and Business University Chongqing401520 China Institute of Nonlinear Analysis Research Changjiang Normal University Chongqing400803 China School of Mathematics and Computer Science Panzhihua University Panzhihua617000 China

In this paper, a new concept, the fuzzy rate of an operator in linear spaces is proposed for the very first time. Some properties and basic principles of it are studied. Fuzzy rate of an operator B which is specific i... 详细信息

关键词： Membership functions

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