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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Shang-Lin Wu Yu-Ting Liu Kuang-Pen Chou Yang-Yin Lin Jie Lu Guangquan Zhang Chun-Hsiang Chuang Wen-Chieh Lin Chin-Teng Lin Brain Research Center Institute of Electrical Control Engineering Institute of Computer Science and Engineering Electronic Systems Research Division National Chung-Shan Institute of Science and Technology (NCSIST) Taoyuan Taiwan Faculty of Engineering and Information Technology University of Technology Sydney Sydney Australia Department of Computer Science National Chiao-Tung University Hsinchu Taiwan

ISBN: (纸本)9781509006274

A brain-computer interface (BCI) system provides a convenient means of communication between the human brain and a computer, which is applied not only to healthy people but also for people that suffer from motor neuron diseases (MNDs). Motor imagery (MI) is one well-known basis for designing Electroencephalography (EEG)-based real-life BCI systems. However, EEG signals are often contaminated with severe noise and various uncertainties, imprecise and incomplete information streams. Therefore, this study proposes spectrum ensemble based on swam-optimized fuzzy integral for integrating decisions from sub-band classifiers that are established by a sub-band common spatial pattern (SBCSP) method. Firstly, the SBCSP effectively extracts features from EEG signals, and thereby the multiple linear discriminant analysis (MLDA) is employed during a MI classification task. Subsequently, particle swarm optimization (PSO) is used to regulate the subject-specific parameters for assigning optimal confidence levels for classifiers used in the fuzzy integral during the fuzzy fusion stage of the proposed system. Moreover, BCI systems usually tend to have complex architectures, be bulky in size, and require time-consuming processing. To overcome this drawback, a wireless and wearable EEG measurement system is investigated in this study. Finally, in our experimental result, the proposed system is found to produce significant improvement in terms of the receiver operating characteristic (ROC) curve. Furthermore, we demonstrate that a robotic arm can be reliably controlled using the proposed BCI system. This paper presents novel insights regarding the possibility of using the proposed MI-based BCI system in real-life applications.

关键词： Electroencephalography Feature extraction Wireless sensor networks Wireless communication Electrodes Particle swarm optimization Microcontrollers

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Driving fatigue prediction with pre-event electroencephalography (EEG) via a recurrent fuzzy neural network

Driving fatigue prediction with pre-event electroencephalogr...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Yu-Ting Liu Shang-Lin Wu Kuang-Pen Chou Yang-Yin Lin Jie Lu Guangquan Zhang Wen-Chieh Lin Chin-Teng Lin Brain Research Center Institute of Electrical Control Engineering Institute of Computer Science and Engineering Electronic Systems Research Division National Chung-Shan Institute of Science and Technology (NCSIST) Taoyuan Taiwan FacuIty of Engineering and Information Technology University of Technology Sydney Sydney Australia Department of Computer Science National Chiao-Tung University Hsinchu Taiwan

ISBN: (纸本)9781509006274

We propose an electroencephalography (EEG) prediction system based on a recurrent fuzzy neural network (RFNN) architecture to assess drivers' fatigue degrees during a virtual-reality (VR) dynamic driving environment. Prediction of fatigue degrees is a crucial and arduous biomedical issue for driving safety, which has attracted growing attention of the research community in the recent past. Meanwhile, combined with the benefits of measuring EEG signals facilitates, many EEG-based brain-computer interfaces (BCIs) have been developed for use in real-time mental assessment. In the literature, EEG signals are severely blended with stochastic noise; therefore, the performance of BCIs is constrained by low resolution in recognition tasks. For this rationale, independent component analysis (ICA) is usually used to find a source mapping from original data that has been blended with unrelated artificial noise. However, the mechanism of ICA cannot be used in real-time BCI design. To overcome this bottleneck, the proposed system in this paper utilizes a recurrent self-evolving fuzzy neural work (RSEFNN) to increase memory capability for adaptive noise cancellation when assessing drivers' mental states during a car driving task. The experimental results without the use of ICA procedure indicate that the proposed RSEFNN model remains superior performance compared with the state-of-the-arts models.

关键词： Electroencephalography Fatigue Real-time systems Vehicles Fuzzy neural networks Signal processing algorithms Integrated circuits

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Online policy iterations for optimal control of input-saturated systems

Online policy iterations for optimal control of input-satura...

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American control Conference

作者： Simone Baldi Giorgio Valmorbida Antonis Papachristodoulou Elias B. Kosmatopoulos Delft Center for Systems and Control Delft University of Technology 2628CD The Netherlands Department of Engineering Science Control Group University of Oxford Parks Road OX1 3PJ U.K. Dept. of Electrical and Computer Engineering Democritus University of Thrace Xanthi 67100 Greece

ISBN: (纸本)9781467386838

This work proposes an online policy iteration procedure for the synthesis of sub-optimal control laws for uncertain Linear Time Invariant (LTI) Asymptotically Null-controllable with Bounded Inputs (ANCBI) systems. The proposed policy iteration method relies on: a policy evaluation step with a piecewise quadratic Lyapunov function in both the state and the deadzone functions of the input signals;a policy improvement step which guarantees at the same time close to optimality (exploitation) and persistence of excitation (exploration). The proposed approach guarantees convergence of the trajectory to a neighborhood around the origin. Besides, the trajectories can be made arbitrarily close to the optimal one provided that the rate at which the the value function and the control policy are updated is fast enough. The solution to the inequalities required to hold at each policy evaluation step can be efficiently implemented with semidefinite programming (SDP) solvers. A numerical example illustrates the results.

关键词： Optimal control Linear systems Convergence Asymptotic stability Lyapunov methods Estimation Trajectory trajectory Optimal control Lyapunov methods asymptotic stability region Linear system Converge iterative methods control strategy Policies

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Robust Decentralized control of Interconnected Nonlinear Systems Subject to Uncertainties and Disturbances via Generalized Extended State Observers 34

Robust Decentralized Control of Interconnected Nonlinear Sys...

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第三十四届中国控制会议

作者： ZHANG Chuanlin YANG ning HE Shuaipeng JIA Ruting Shanghai Engineering Research Center of Intelligent Management and Control for Power Process College of Automation EngineeringShanghai University of Electric Power Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Electrical and Computer Engineering Department California State University

ISBN: (纸本)9789881563897

This paper studies the problem of robust decentralized control for a class of large-scale interconnected systems subject to uncertainties and disturbances via a generalized active disturbance rejection control method. First, a novel extended state observer(ESO) is constructed separately for each subsystem with less dependence of the precise system information and structure. Second, an explicit formula of the decentralized active disturbance rejection control(DADRC) law is presented by utilizing the output feedback domination approach. It is shown that by a delicate analysis procedure, the closed-loop system can be rendered semi-globally asymptotically stable only using decentralized output feedback anti-disturbance controller. Numerical simulations show the efficiency of the proposed method.

关键词： output feedback control global stabilization disturbance rejection control extended state observer

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Counterattack detection in broadcast soccer videos using camera motion estimation

Counterattack detection in broadcast soccer videos using cam...

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2015 International Symposium on Artificial Intelligence and Signal Processing, AISP 2015

作者： Sigari, Mohamad-Hoseyn Soltanian-Zadeh, Hamid Kiani, Vahid Pourreza, Amid-Reza Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Machine Vision Research Laboratory Computer Engineering Department Faculty of Engineering Ferdowsi University of Mashhad Mashhad Iran

ISBN: (纸本)9781479988174

This paper presents a new method for counterattack detection using estimated camera motion and evaluates some classification methods to detect this event. To this end, video is partitioned to shots and view type of each shot is recognized first. Then, relative pan of the camera during far-view and medium-view shots is estimated. After weighting of pan value of each frame according to the type of shots, the video is partitioned to motion segments. Then, motion segments are refined to achieve better results. Finally, the features extracted from consecutive motion segments are investigated for counterattack detection. We propose two methods for counterattack detection: (1) rule-based (heuristic rules) and (2) SVM-based. Experiments show that the SVM classifier with linear or RBF kernel results in the best results. © 2015 IEEE.

关键词： Motion estimation

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TOWARD PERCEPTUAL DEEP LEARNING–BASED ABNORMAL BEHAVIOR PATTERN ANALYSIS FOR PATIENTS WITH ALZHEIMER’S DISEASE

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Alzheimer's & Dementia 2018年第7期14卷 P548-P548页

作者： Jeonghwan Gwak Jong-In Song Kiseon Kim Moongu Jeon Cheolbin Park Hyunsu Jeong Kyu Yeong Choi Jung Eun Park Jung Sup Lee Byeong Chae Kim Kun Ho Lee Biomedical Research Institute & Department of Radiology Seoul National University Hospital Seoul Republic of South Korea School of Electrical Engineering and Computer Science Gwangju Institute of Science and Technology Gwangju Republic of South Korea Department of Premedics Chosun University Gwangju Republic of South Korea BK21-plus Research Team for Bioactive Control Technology Chosun University Gwangju Republic of South Korea Department of Life Science Chosun University Gwangju Republic of South Korea Department of Biomedical Science Chosun University Gwangju Republic of South Korea National Research Center for Dementia Chosun University Gwangju Republic of South Korea Department of Neurology Chonnam National University Medical School Gwangju Republic of South Korea

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P1-559: TOWARD PERCEPTUAL DEEP LEARNING–BASED ABNORMAL BEHAVIOR PATTERN ANALYSIS FOR PATIENTS WITH ALZHEIMER'S DISEASE

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Alzheimer's & Dementia 2018年第7S_PART_10期14卷

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Enhancing quantum control by bootstrapping a quantum processor of 12 qubits

arXiv

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arXiv 2017年

作者： Lu, Dawei Li, Keren Li, Jun Katiyar, Hemant Park, Annie Jihyun Feng, Guanru Xin, Tao Li, Hang Long, Guilu Brodutch, Aharon Baugh, Jonathan Zeng, Bei Laflamme, Raymond Department of Physics Southern University of Science and Technology Shenzhen518055 China Institute for Quantum Computing Department of Physics and Astronomy University of Waterloo WaterlooONN2L 3G1 Canada State Key Laboratory of Low-Dimensional Quantum Physics Department of Physics Tsinghua University Beijing100084 China Beijing Computational Science Research Center Beijing100193 China Max-Planck-Institutfür Quantenoptik GarchingD-85748 Germany Center for Quantum Information and Quantum Control Department of Physics Department of Electrical and Computer Engineering University of Toronto TorontoONM5S 3H6 Canada Department of Mathematics and Statistics University of Guelph GuelphONN1G 2W1 Canada Perimeter Institute for Theoretical Physics Waterloo ONN2L 2Y5 Canada

Accurate and efficient control of quantum systems is one of the central challenges for quantum information processing. Current state-of-the-art experiments rarely go beyond 10 qubits and in most cases demonstrate only limited control. Here we demonstrate control of a 12-qubit system, and show that the system can be employed as a quantum processor to optimize its own control sequence by using measurement-based feedback control (MQFC). The final product is a control sequence for a complex 12-qubit task: preparation of a 12-coherent state. The control sequence is about 10% more accurate than the one generated by the standard (classical) technique, showing that MQFC can correct for unknown imperfections. Apart from demonstrating a high level of control over a relatively large system, our results show that even at the 12-qubit level, a quantum processor can be a useful lab instrument. As an extension of our work, we propose a method for combining the MQFC technique with a twirling protocol, to optimize the control sequence that produces a desired Clifford gate. Copyright © 2017, The Authors. All rights reserved.

关键词： Quantum optics

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An ultra-high-density 256-channel/25mm2 neural sensing microsystem using TSV-embedded neural probes

An ultra-high-density 256-channel/25mm2 neural sensing micro...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Yu-Chieh Huang Po-Tsang Huang Shang-Lin Wu Yu-Chen Hu Yan-Huei You Ming Chen Yan-Yu Huang Hsiao-Chun Chang Yen-Han Lin Jeng-Ren Duann Tzai-Wen Chiu Wei Hwang Kuan-Neng Chen Ching-Te Chuang Jin-Chern Chiou Institute of Electrical Control Engineering National Chiao Tung University Hsinchu Taiwan Department of Electrical and Computer Engineering National Chiao Tung University Hsinchu Taiwan Department of Electronics Engineering National Chiao Tung University Hsinchu Taiwan National Chiao Tung University Hsinchu TW BME R&D Center China Medical University Taiwan Department of Biological Science and Technology National Chiao Tung University Hsinchu Taiwan

ISBN: (纸本)9781479953424

Highly integrated neural sensing microsystems are crucial to capture accurate signals for brain function investigations. In this paper, a 256-channel/25 mm2 neural sensing microsystem is presented based on through-silicon-via (TSV) 2.5D integration. This microsystem composes of dissolvable μ-needles, TSV-embedded μ-probes, 256-channel neural amplifiers, 11-bit area-power-efficient SAR ADCs and serializers. Based on the dissolvable μ-needles and TSV 2.5D integration, this microsystem can detect 256 ECoG/LFP signals within the small area of 5mm × 5mm. Additionally, the neural amplifier realizes 57.8dB gain with only 9.8μW for each channel, and the 9.7-bit ENOB of the SAR ADC at 32kS/s can be achieved with 0.42μW and 0.036 mm2. The overall power of this microsystem is only 3.79mW for 256-channel neural sensing.

关键词： Sensors Through-silicon vias Voltage control Bonding Probes Tuning Power demand

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control on a molecular scale: A perspective

Control on a molecular scale: A perspective

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American control Conference

作者： Rolf Findeisen Martha A. Grover Christian Wagner Michael Maiworm Ruslan Temirov F. Stefan Tautz Murti V. Salapaka Srinivasa Salapaka Richard D. Braatz S.O. Reza Moheimani Otto-von-Guericke-Universit?t Magdeburg Laboratory for Systems Theory and Automatic Control Germany School of Chemical & Biomolecular Engineering Georgia Institute of Technology USA Peter Gruenberg Institute (PGI-3) Juelich Research Center Germany Electrical and Computer Engineering Department University of Minnesota USA Massachusetts Institute of Technology USA Department of Mechanical Engineering The University of Texas at Dalla USA

ISBN: (纸本)9781467386838

Imaging and manipulating objects down to the molecular level plays a crucial role in many disciplines. It allows to unravel molecular phenomena, to form materials with new chemical and physical properties, or to build objects on an atomic scale. Science on the nanoscale is inherently interdisciplinary. It requires knowledge and insight into many fields, spanning from modeling, measuring, imaging, actuation to control. Often feedback control facilitates operation with molecular precision, despite the fact that many physical phenomena at the molecular level are still not well understood, and that stochastic and nonlinear effects are inherently present. This work provides an insight into some of the current control related research activities on a molecular scale. This is done considering examples from different fields: control related to scanning probe microscopy such as atomic force microscopy, controlled self assembly on a molecular scale, control aspects of molecular transport, and the use of control for manipulation of single molecules using macroscopic probe tips. The hope is that control related researchers, who are not experts in these fields, become aware of the opportunities present, which could also drive new theoretical developments.

关键词： computational modeling Mathematical model Force Atomic force microscopy Numerical models computational modeling Atomic Force Microscopy numerical models Mathematical Model Force Standing Orders Scale formation Insight Transport Process Physical Phenomena Scanning Probe Microscopy Hopefulness Research Activities chemical and physical properties feedback control

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