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Transfer Learning for EEG-Based Brain-computer Interfaces: A Review of Progress Made Since 2016

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arXiv 2020年

作者： Wu, Dongrui Xu, Yifan Lu, Bao-Liang The Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China The Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Brain Science and Technology Research Center Qing Yuan Research Institute Shanghai Jiao Tong University 800 Dong Chuan Road Shanghai200240 China

A brain-computer interface (BCI) enables a user to communicate with a computer directly using brain signals. The most common non-invasive BCI modality, electroencephalogram (EEG), is sensitive to noise/artifact and suffers between-subject/within-subject non-stationarity. Therefore, it is difficult to build a generic pattern recognition model in an EEG-based BCI system that is optimal for different subjects, during different sessions, for different devices and tasks. Usually, a calibration session is needed to collect some training data for a new subject, which is time-consuming and user unfriendly. Transfer learning (TL), which utilizes data or knowledge from similar or relevant subjects/sessions/devices/tasks to facilitate learning for a new subject/session/device/task, is frequently used to reduce the amount of calibration effort. This paper reviews journal publications on TL approaches in EEG-based BCIs in the last few years, i.e., since 2016. Six paradigms and applications - motor imagery, event-related potentials, steady-state visual evoked potentials, affective BCIs, regression problems, and adversarial attacks - are considered. For each paradigm/application, we group the TL approaches into cross-subject/session, cross-device, and cross-task settings and review them separately. Observations and conclusions are made at the end of the paper, which may point to future research directions. Copyright © 2020, The Authors. All rights reserved.

关键词： Brain computer interface

Electric power supply of steel producing companies: Schematic design solutions to improve reliability of power grids

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AIP Conference Proceedings 2022年第1期2686卷

作者： Gennady P. Kornilov Ildar R. Abdulveleev Oxana S. Logunova Palvan I. Kalandarov Obid Tursunov Dilshod Kodirov Doniyor Abdurakhimov 1Department of Power Supply of Industrial Enterprises Nosov Mangnitogorsk State Technical University Magnitogorsk Russia 2Department of Computer Engineering and Programming Nosov Mangnitogorsk State Technical University Magnitogorsk Russia 3Department of Automation and Control of Technological Process and Production Tashkent Institute of Irrigation and Agricultural Mechanization Engineers 100000 Tashkent Uzbekistan 4Department of Power Supply and Renewable Energy Sources Tashkent Institute of Irrigation and Agricultural Mechanization Engineers 100000 Tashkent Uzbekistan 5Research Institute of Forestry 111104 Tashkent Uzbekistan 6Gulistan State University 120100 Gulistan Uzbekistan

This research is aimed at improving electric power supply reliability at major industrial plants by applying schematic design solutions. The authors analyzed the features of branch electric power distribution systems at a metallurgical plant; considered options of their revamping to improve reliability of electric power supply; carried out experimental research on splitting 110 kV meshed system at the integrated iron and steel works. When performing the research, mathematical simulation methods and full-scale experiment methods were used. Following the research, we proposed three options to revamp the power grid at the industrial plant applying schematic design solutions: Scheme A - separating substations, causing problems, in an individual block; Scheme B - separating independent 110 kV closed electric power grids; Scheme C – splitting the meshed system into two independent circuits. It is proved that the most efficient solution is Scheme C, which is characterized by a lower number of unscheduled downtimes of the facilities by mitigating the effects of faults in one of meshed systems on a continuous operation of shops powered from the neighboring grid; eliminated risks of simultaneous stops of all or the majority of metallurgical shops of the works during short circuits in 110 kV grids; and a considerable reduction in short circuit currents and active losses in 110 kV industrial grids. An aggregate benefit from the proposed measures aimed at revamping of the electrical grid of metallurgical units by applying schematic design solutions is over USD750,000/year.

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A comparative study above two self-tuning controllers with aplication to the control of synchronous generator excitation system

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arXiv 2018年

作者： Filip, Ioan Curiac, Daniel Prostean, Octavian Szeidert, Iosif "Politehnica" University of Timisoara Faculty of Control Engineering and Computer Sciences Department of Automation and Industrial Informatics

This paper presents two self-tuning control structures synthesized through the minimization of two criterion functions. It is described the computation methodology of the control laws, both being particularized for the case of the synchronous generator's excitation control. The parameters estimator is considered the recursive least square error (RLSE) algorithm. In order to validate the considered control structures, two comparative study cases by computer simulation are presented. Copyright © 2018, The Authors. All rights reserved.

关键词： Adaptive control systems

Semi-global leader-following output consensus of discrete-time linear multi-agent systems with input saturation

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Semi-global leader-following output consensus of discrete-ti...

2018 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2018

作者： Shi, Liangren Li, Yuanlong Lin, Zongli Brown, Charles L. Innovation Center Department of Automation Shanghai Jiao Tong University China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Department of Automation Shanghai Jiao Tong University China Department of Electrical and Computer Engineering University of Virginia P.O. Box 400743 CharlottesvilleVA22904-4743 United States

ISBN: (纸本)9781538668689

We consider the problem of semi-global leader-following output consensus for a group of agents, consisting of a leader agent and some follower agents, which are described by discrete-time linear systems and connected on a directed network. For each follower agent, a distributed observer is built that estimates the state of the leader. Based on the estimates of the leader state and the solution of a parameterized algebraic Riccati equation, we design low gain consensus protocols that are shown to solve the semi-global output consensus problem as long as the leader agent is reachable globally on the network. Numerical simulation shows the performance of the proposed consensus protocols. © 2018 IEEE.

关键词： Multi agent systems

Scheduling for Re-entrant Hybrid Flowshop Based on Wolf Pack Algorithm

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Scheduling for Re-entrant Hybrid Flowshop Based on Wolf Pack...

2018 International Conference on Advanced Materials, Intelligent Manufacturing and automation, AMIMA 2018

作者： Han, Zhonghua Tian, Xutian Ma, Xiaofu Lin, Shuo Faculty of Information and Control Engineering Shenyang Jianzhu University Liaoning110168 China Digital Factory Department Shenyang Institute of Automation CAS Shenyang110016 China Information and Control Engineering Faculty Shenyang Jianzhu University Liaoning110168 China Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA24060 United States

In order to solve the scheduling problems of Re-entrant Hybrid Flowshop (RHFS), this paper investigates the mathematical programming model of RHFS, and proposes the wolf pack based algorithm (WPA) as a global optimization method. Multi-Sticking Crape Masking procedure scheduling problems in painting workshop of a bus manufacturing enterprise are of typical features of RHFS. We regard it as an application objective of the proposed algorithm, applying WPA and multiple evolutionary algorithms to solve the problems. The results show that the algorithm can solve re-entrant scheduling problems of hybrid flowshop more effectively compared with other conventional methods. © Published under licence by IOP Publishing Ltd.

关键词： Global optimization

Blockchain Technology Based Decentralized Energy Trading for Multiple-Microgrid Systems

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Blockchain Technology Based Decentralized Energy Trading for...

IEEE Conference on Energy Internet and Energy System Integration (EI2)

作者： Ting Li Wei Zhang Ning Chen Minhui Qian Ying Xu School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China EPRI Nanjing China Department of Electrical Engineering & Computer Science University of Central Florida Orlando USA

ISBN: (数字)9781728131375

ISBN: (纸本)9781728131382

With the emerging technology for distributed generation and urge of improving quality of service of power supply for energy users, more and more Microgrids (MGs) are integrated into the distributed networks to serve the energy users. These Microgrids are gradually formulating a Multi-Microgrid System (MMGS, Multi-Microgrid System), which will play an important role for the future energy supply. Building a centralized control center not only increases the expense of investment, but also brings the issues of maintaining fairness among energy users. To address these problems, this paper proposes a peer-to-peer method for energy trading of MMGS, based on the idea of decentralized trading. An auction-based trading mechanism suitable for peer-to-peer energy trading is proposed first. For this mechanism, the MGs firstly declare their energy buying bids or selling quotations. Then, the market-clearing price is determined by using a unified weight clearing algorithm in a decentralized manner. By applying the edge technology of Blockchain, the implementation of the proposed peer-to-peer energy trading method, including the architecture, procedures, security check, etc., is also discussed. The proposed Blockchain-based energy trading platform can realize the decentralized and autonomous energy trading of MGs within an MMGS. A case study with an MMGS with 10 MG units is provided to demonstrate the effectiveness of the proposed approach.

关键词： Peer-to-peer computing Microgrids Blockchain Distributed power generation Electronic commerce Power distribution economics Pricing

An Online Approach to Physical Watermark Design

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arXiv 2019年

作者： Liu, Hanxiao Mo, Yilin Yan, Jiaqi Xie, Lihua Johansson, Karl H. School of Electrical and Electronic Engineering Nanyang Technological University Singapore Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Department of Automation and BNRist Tsinghua University China School of Electrical and Electronic Engineering Nanyang Technological University Singapore Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden

This paper considers the problem of designing physical watermark signals in order to optimally detect possible replay attack in a linear time-invariant system, under the assumption that the system parameters are unknown and need to be identified online. We first provide a replay attack model, where an adversary replays the previous sensor data in order to fool the system. A physical watermarking scheme, which leverages a random control input as a watermark to detect the replay attack, is then introduced. The optimal watermark signal design problem is cast as an optimization problem, which aims to achieve the optimal trade-off between control performance and intrusion detection. An online watermarking design and system identification algorithm is provided to deal with systems with unknown parameters. We prove that the proposed algorithm converges to the optimal one and characterize the almost sure convergence rate. A numerical example and an industrial process example are provided to illustrate the effectiveness of the proposed strategy. Copyright © 2019, The Authors. All rights reserved.

关键词： Intrusion detection

Hierarchic neighbors embedding

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arXiv 2019年

作者： Liu, Shenglan Yu, Yang Liu, Yang Qiao, Hong Feng, Lin Feng, Jiashi School of Computer Science and Technology Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian Liaoning116024 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore

Manifold learning now plays a very important role in machine learning and many relevant applications. Although its superior performance in dealing with nonlinear data distribution, data sparsity is always a thorny knot. There are few researches to well handle it in manifold learning. In this paper, we propose Hierarchic Neighbors Embedding (HNE), which enhance local connection by the hierarchic combination of neighbors. After further analyzing topological connection and reconstruction performance, three different versions of HNE are given. The experimental results show that our methods work well on both synthetic data and high-dimensional real-world tasks. HNE develops the outstanding advantages in dealing with general data. Furthermore, comparing with other popular manifold learning methods, the performance on sparse samples and weak-connected manifolds is better for HNE. Copyright © 2019, The Authors. All rights reserved.

关键词： Topology

An exploratory study on machine learning to couple numerical solutions of partial differential equations

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arXiv 2020年

作者： Tang, Hansong Li, L. Grossberg, M. Liu, Y.J. Jia, Y.M. Li, S.S. Dong, W.B. Civil Engineering Department City College of New York City University of New York New York10031 United States Department of Control Science and Engineering University of Shanghai for Science and Technology Shanghai200093 China Department of Computer Science City College of New York City University of New York New York10031 United States School of Mathematics Georgia Institute of Technology GA30332 United States School of Automation Science and Electrical Engineering Beihang University Beijing10083 China School of Hydraulic and Hydroelectric Engineering Xi'an University of Technology Shaanxi710048 China

As further progress in the accurate and efficient computation of coupled partial differential equations (PDEs) becomes increasingly difficult, it has become highly desired to develop new methods for such computation. In deviation from conventional approaches, this short communication paper explores a computational paradigm that couples numerical solutions of PDEs via machine-learning (ML) based methods, together with a preliminary study on the paradigm. Particularly, it solves PDEs in subdomains as in a conventional approach but develops and trains artificial neural networks (ANN) to couple the PDEs' solutions at their interfaces, leading to solutions to the PDEs in the whole domains. The concepts and algorithms for the ML coupling are discussed using coupled Poisson equations and coupled advection-diffusion equations. Preliminary numerical examples illustrate the feasibility and performance of the ML coupling. Although preliminary, the results of this exploratory study indicate that the ML paradigm is promising and deserves further research. Copyright © 2020, The Authors. All rights reserved.

关键词： Neural networks