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K-Means Clustering-based Kernel Canonical Correlation Analysis for Multimodal Emotion Recognition ⁎

IFAC-PapersOnLine 2020年第2期53卷 10250-10254页

作者： Luefeng Chen Kuanlin Wang Min Wu Witold Pedrycz Kaoru Hirota School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China Department of Electrical and Computer Engineering University of Alberta Edmonton AB T6R 2G7 Canada Tokyo Institute of Technology Yokohama 226-8502 Japan

Emotion is an important part of human interaction. Emotional recognition can greatly promote human-centered interaction techniques. On this basis, multimodal feature fusion can effectively improve the emotion recognition rate. However, in the multimodal feature fusion at the feature level, most of the methods do not consider the intrinsic relationship between different modes. Only the fusion of analysis and transformation of the feature matrices of different modes does not make better use of modal differences to improve the recognition rate. This problem led us to propose feature fusion method based on K-Means clustering and kernel canonical correlation analysis (KCCA). Clustering makes the classification of features not classified by mode, but by the degree of influence on emotional labels, thus positively affecting the results of KCCA. The experimental results obtained on the Savee database show that the proposed K-Means based KCCA improves overall classification performance and produces higher recognition rate than that of the state of art methods, such as the Informed Segmentation and Labeling Approach.

关键词： Emotion Recognition K-Means Clustering Kernel Canonical Correlation Analysis Feature Fusion

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An Adaptive Federated control Strategy for Participant Selection in Multi-Client Collaboration

An Adaptive Federated Control Strategy for Participant Selec...

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Yizhu Chen Xiaoming Du Xiao Wang Jun Jason Zhang Fei-Yue Wang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China School of Economics and Management University of Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China School of Electrical Engineering and Automation Wuhan University Wuhan China

The federated ecology provides a new paradigm for breaking the isolated data island problem and fully activating the potential of big data and artificial intelligence, especially in multi-client collaboration tasks. Participant selection strategy in multi-client collaboration is the main limitation for increasing the convergence speed and lowing the communication costs. However, in the face of the unbalanced and non-IID data distributions, the performance of federated optimization algorithms will also decrease. To solve the above problems, we propose an adaptive federated control strategy for participant selection in multi-client collaboration based on the Mann-Kendall test, named FedMK. By adaptively selecting weak participants for training rather than random selection, FedMK can speed up model convergence and reduce communication costs. Experiment results show that our method outperforms the baseline method in non-IID scenarios, and the number of communication rounds on CIFAR-10 and synthetic datasets reduced by more than 15% and 10 %,9 respectively.

关键词： Training Adaptation models Costs Biological system modeling Collaboration Optimization methods Ecology

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A Bioinspired retinal neural network for accurately extracting small-target motion information in cluttered backgrounds

arXiv

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arXiv 2021年

作者： Huang, Xiao Qiao, Hong Li, Hui Jiang, Zhihong School of Mechatronical Engineering Advanced Innovation Center for Intelligent Robots and Systems Key Laboratory of Biomimetic Robots and Systems of Chinese Ministry of Education Beijing Institute of Technology Beijing100081 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Beijing Key Laboratory of Research and Application for Robotic Intelligence of’Hand-Eye-Brain’ Interaction Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China

—Robust and accurate detection of small moving targets in cluttered moving backgrounds is a significant and challenging problem for robotic visual systems to perform search and tracking tasks. Inspired by the neural circuitry of elementary motion vision in the mammalian retina, this paper proposes a bioinspired retinal neural network based on a new neurodynamics-based temporal filtering and multiform 2-D spatial Gabor filtering. This model can estimate motion direction accurately via only two perpendicular spatiotemporal filtering signals, and respond to small targets of different sizes and velocities through adjusting the dendrite field size of spatial filter. Meanwhile, an algorithm of directionally selective inhibition is proposed to suppress the target-like features in the moving background, which can reduce the influence of background motion effectively. Extensive synthetic and real-data experiments show that the proposed model works stably for small targets of a wider size and velocity range, and has better detection performance than other bioinspired models. Additionally, it can also extract the information of motion direction and motion energy accurately and rapidly. Copyright © 2021, The Authors. All rights reserved.

关键词： Ophthalmology

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A Bioinspired approach-sensitive neural network for collision detection in cluttered and dynamic backgrounds

arXiv

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arXiv 2021年

—Rapid, accurate and robust detection of looming objects in cluttered moving backgrounds is a significant and challenging problem for robotic visual systems to perform collision detection and avoidance tasks. Inspired by the neural circuit of elementary motion vision in the mammalian retina, this paper proposes a bioinspired approach-sensitive neural network (ASNN) that contains three main contributions. Firstly, a direction-selective visual processing module is built based on the spatiotemporal energy framework, which can estimate motion direction accurately via only two mutually perpendicular spatiotemporal filtering channels. Secondly, a novel approach-sensitive neural network is modeled as a push-pull structure formed by ON and OFF pathways, which responds strongly to approaching motion while insensitivity to lateral motion. Finally, a method of directionally selective inhibition is introduced, which is able to suppress the translational backgrounds effectively. Extensive synthetic and real robotic experiments show that the proposed model is able to not only detect collision accurately and robustly in cluttered and dynamic backgrounds but also extract more collision information like position and direction, for guiding rapid decision making. © 2021, CC BY.

关键词： Mammals

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Trajectory Planning and Tracking control for Positioning of Planar Three-link Underactuated Manipulator

Trajectory Planning and Tracking Control for Positioning of ...

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Asian control Conference

作者： Zixin Huang Xuzhi Lai Pan Zhang Min Wu Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China School of Automation China University of Geosciences Wuhan China

ISBN: (纸本)9781728102634

This paper is concerned with the position control problem of the planar active-passive-active (APA) underactuated manipulator, whose dynamic constraint is mainly caused by the second-order nonholonomic constraint. First, the dynamic model of the system is established and the target angles of the three links are calculated by using differential evolution algorithm. Then, we present a trajectory planning and tracking control strategy to realize the control objective, which is to stabilize the end-point from any initial position to the target position. We plan two stage trajectories, the first of which is planned for the active links. When the the active links track the first stage trajectories, they can reach to their target angles. The second one is planned for the first active link based on the differential evolution algorithm. When the first active link tracks the second stage trajectory, it will back to its target angle eventually. Meantime, the passive link will be controlled to its target angle. Then, we design sliding mode variable structure controllers to make active links track the planned trajectories, which can make the all links reach to the their target angles. Finally, numerical simulation results illuminate the effectiveness of the proposed strategy.

关键词： Trajectory Manipulators Target tracking Position control Planning Heuristic algorithms Optimization

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FCM-RDpA: TSK fuzzy regression model construction using fuzzy C-means clustering, regularization, droprule, and powerball adabelief

arXiv

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arXiv 2020年

作者： Shi, Zhenhua Wu, Dongrui Guo, Chenfeng Zhao, Changming Cui, Yuqi Wang, Fei-Yue Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

To effectively optimize Takagi-Sugeno-Kang (TSK) fuzzy systems for regression problems, a mini-batch gradient descent with regularization, DropRule, and AdaBound (MBGD-RDA) algorithm was recently proposed. This paper further proposes FCM-RDpA, which improves MBGD-RDA by replacing the grid partition approach in rule initialization by fuzzy c-means clustering, and AdaBound by Powerball AdaBelief, which integrates recently proposed Powerball gradient and AdaBelief to further expedite and stabilize parameter optimization. Extensive experiments on 22 regression datasets with various sizes and dimensionalities validated the superiority of FCM-RDpA over MBGD-RDA, especially when the feature dimensionality is higher. We also propose an additional approach, FCM-RDpAx, that further improves FCM-RDpA by using augmented features in both the antecedents and consequents of the rules. Copyright © 2020, The Authors. All rights reserved.

关键词： Gradient methods

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Design of Smart Home Monitoring and control System Based on Zigbee and WIFI

Design of Smart Home Monitoring and Control System Based on ...

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第三十八届中国控制会议

作者： Chentao Li Kaifeng Dong Fang Jin Junlei Song Wenqin Mo School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Smart Home system is the use of home life associated with hardware and related application technology, the introduction of home appliance automation, remote control, intelligent processing technology in a traditional home environment, to design a provide users with comprehensive information exchange capabilities, in order to enhanced home life safety, comfort and convenience of home systems. At present, there are problems such as complicated wiring, single service, and high price in this field. In response to these problems, this paper designs a smart home system based on Zigbee and WIFI. The system consists of a terminal node, a gateway node and a remote control terminal. The terminal node and the gateway node form a home internal network through Zigbee technology, and the remote control terminal accesses and controls the home internal network through WIFI.

关键词： Smart home Zigbee WIFI Wireless transmission Remote control

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control System Design for Weight on Bit in complex Geological Drilling Process

Control System Design for Weight on Bit in Complex Geologica...

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第三十八届中国控制会议

作者： Sike Ma Min Wu Jun Cheng Luefeng Chen School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

With the increase in drilling depth, the encountered formations become more complicated, and industrial controller for weight on bit has limited precision due to the uncertain and varying formations. In this paper, we design a scheme of control system for weight on bit to achieve higher control precision in complex geological drilling process. A double-loop control structure is introduced, which involves with two system models: a multi-degree-of-freedom lumped parameter drill string model and a finite element bit-rock interaction model. The effect of varying formations on weight on bit is analyzed, and a control strategy for control system is presented in this paper.

关键词： Drilling process weight on bit control system drill string model bit-rock interaction model uncertain formations

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Position Solution and Motion Simulation for Rock Drilling Arm

Position Solution and Motion Simulation for Rock Drilling Ar...

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第三十八届中国控制会议

作者： Zhilin Tang Jianqi An School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Drilling rigs are key devices in tunnel projects, which dig holes on a rock face by drilling arms. The quality and efficiency of tunnel constructions are directly determined by the positioning accuracy of the holes and time for traversing all the holes. This paper provides a complete solution for trajectory planning with accuracy and efficiency. First, this paper analyzes the structure of a drilling arm, establishes a forward kinematic model of the drilling arm by Denavit-Hartenberg convention. Next,to solve the inverse kinematics problem of drilling arm, a particle swarm optimization with adaptive inertia weight is ***, an optimal drilling sequence is found based on Hopfield network. Thereafter, a quintic polynomial method has been adopted to calculate the trajectory of the drilling arm. Finally, results of simulations show that the solution satisfies the accuracy of positioning and calculates the optimal trajectory.

关键词： inverse kinematic robot manipulator trajectory planning particle swarm optimization

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Stability Analysis of Nonlinear Teleoperation systems With Time-Varying Delays Via A Delay-Product-Type Functional

Stability Analysis of Nonlinear Teleoperation Systems With T...

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第三十八届中国控制会议

作者： Xiao-Hui Guo Chuan-Ke Zhang Yong He School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

This paper is concerned with the stability analysis of a class of nonlinear teleoperation systems with time-varying delays. The proportional derivative position position control scheme with asymmetrical time-varying delays in control loops is considered for the master and the slave robots. Firstly, a new Lyapunov-Krasovskii functional（LKF） with several delayproduct-type terms is constructed by using the information of asymmetrical time-varying delays;and the Wirtinger-based integral inequality and the reciprocally convex matrix inequality are used to estimate the derivative of the LKF. As a result, a delaydependent stability criterion with less conservatism is established. Finally, an example is given to show the effectiveness and merits of the proposed criterion.

关键词： Nonlinear teleoperation system time-varying delay stability analysis linear matrix inequality

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