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3rd International Symposium on intelligent Information Technology Application Workshops, IITAW 2009

作者： Li, Wei Huang, Yue Xu, Jiang Chen, Xi Wang, Xiaojun Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780769538600

Electroencephalography (EEG) is widely used in the field of neural engineering. EEG signals can describe the brain activities while the subjects with para/tetraplegia perform movement with their limbs. This paper reviews the research on the design of experiment, the different frequency bands of EEG signals and the data processing methods of EEG. According to the analysis of the previous studies, it has been concluded that EEG signal of alpha and beta frequency bands is of special significance for analyzing the brain activity of subjects with SCI during movements. And EEG signals also can be used for BCI with application in rehabilitation engineering. © 2009 IEEE.

关键词： Electroencephalography

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EMPIRICAL STUDIES ON THE PROPERTIES OF LINEAR REGIONS IN DEEP NEURAL NETWORKS 8

EMPIRICAL STUDIES ON THE PROPERTIES OF LINEAR REGIONS IN DEE...

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8th International Conference on Learning Representations, ICLR 2020

作者： Zhang, Xiao Wu, Dongrui 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

A deep neural network (DNN) with piecewise linear activations can partition the input space into numerous small linear regions, where different linear functions are fitted. It is believed that the number of these regions represents the expressivity of the DNN. This paper provides a novel and meticulous perspective to look into DNNs: Instead of just counting the number of the linear regions, we study their local properties, such as the inspheres, the directions of the corresponding hyperplanes, the decision boundaries, and the relevance of the surrounding regions. We empirically observed that different optimization techniques lead to completely different linear regions, even though they result in similar classification accuracies. We hope our study can inspire the design of novel optimization techniques, and help discover and analyze the behaviors of DNNs. © 2020 8th International Conference on Learning Representations, ICLR 2020. All rights reserved.

关键词： Deep neural networks

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ANN based three-value logic SVPWM control in CSR

ANN based three-value logic SVPWM control in CSR

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2010 IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2010

作者： Xu, Jinbang Shen, Anwen Wu, Zhizhuo Yang, Jun Yang, Xuan Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Department of Control Science and Technology Huazhong University of Science and Technology 430074 Wuhan China

ISBN: (纸本)9781424464388

To achieve better performance with various load and system parameters in controlling a current-source rectifier (CSR) with less computing cost, a neural-network-based implementation of three-logic space-vector modulation (SVM) is proposed in this research, and the random weight change (RWC)algorithm is employed for on-line parameter tuning. The scheme has been simulated in SABER simulation software and the result is compared with the conventional SVM method. The advantage of the method is explicit with a better performance under a non-rated system load. © 2010 IEEE.

关键词： Vector spaces

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Bimodal Feature Propagation and Fusion for Real-time Semantic Segmentation on RGB-D images 7

Bimodal Feature Propagation and Fusion for Real-time Semanti...

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7th International Conference on intelligent Computing and Signal processing, ICSP 2022

作者： He, Ying Xiao, Li Sun, Zhigang Wang, Zhuo Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Wuhan China

ISBN: (纸本)9781665478571

Semantic Segmentation is the foundation of scene understanding and automatic driving tasks. One of the challenges of semantic segmentation is the reduction of feature resolution as the network goes deep. In this paper, the low-resolution features are integrated into high-resolution features progressively, enabling high-resolution prediction. Currently, incorporating the auxiliary depth information into a semantic segmentation framework has proven to be helpful to improve accuracy. However, additional process of depth data immensely increases computational complexity, resulting in limitation for practical application. Here, a real-time bimodal semantic segmentation network that effectively extracts and fuses complementary information is investigated. Our network extends a light-weight architecture which can seamlessly take advantage of various prevalent backbone networks. Our model extracts RGB and depth features from two branches in parallel and integrates multi-level features of two modalities through bimodal feature fusion blocks. To reduce computation complexity, we employ depth-wise separable convolution while keep performance intact. Meanwhile, an attention mechanism is exploited to recalibrate the fusion modality features adaptively. Refinement components are retained to refine multi-resolution feature maps. We conduct ablative study to demonstrate the availability of our bimodal fusion blocks. Comprehensive experiments validate that the proposed network outperforms the state-of-the-arts and achieves 18 FPS on the challenging RGB-D dataset, NYUDv2. © 2022 IEEE.

关键词： Semantic Segmentation

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Demand-Side Frequency control in Power Network Based on Multi-Agent Deep Reinforcement Learning 5

Demand-Side Frequency Control in Power Network Based on Mult...

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5th International Conference on Industrial Artificial Intelligence, IAI 2023

作者： Liu, Xianggang Liu, Zhi-Wei Chi, Ming Zhang, Yifan Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Ministry of Education College of Artificial Intelligence and Automation Wuhan China

ISBN: (纸本)9798350325294

The integration of renewable energy sources into the power grid has led to new challenges in maintaining the stability of the system frequency. This paper proposes a novel approach to address the Optimal Demand Side Frequency control (ODFC) problem using Multi-Agent Deep Deterministic Policy Gradient (MADDPG) method. The proposed method models the ODFC problem as a Markov game, with centralized training based on multi-agent cooperative self-learning and associative storage service. In the decentralized execution stage, each agent independently outputs control actions to the controlled plant using local observations. Numerical simulations show that the proposed method effectively addresses the ODFC problem with superior performance compared to traditional methods. © 2023 IEEE.

关键词： Numerical methods

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FSM model and analysis for reconfigurable protocol stack in networked control system

FSM model and analysis for reconfigurable protocol stack in ...

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2010 8th IEEE International Conference on control and Automation, ICCA 2010

作者： Chen, Hui Zhou, Chunjie Ma, Jie Qing, Yuanqing Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Techonolgy Wuhan Hubei 430074 China

ISBN: (纸本)9781424451951

The protocol stack plays a critical role in determining the performance of networked control system (NCS), which governs the communication activities and directly affects the communication quality of service (QoS). Full or partial reconfiguration of protocol stack offers both optimized communication service and system performance. This paper proposes a finite state machines (FSMs) approach for modeling analysis of reconfiguration protocols stack in NCS. The proposed reconfiguration architecture is implemented by illustrating a simulation for the flexible scheduling scheme on the Ethernet protocol. Detail FSM implement modules for composing node models of master and salve are discussed respectively in OPNET environment. The simulation results validate the effective of our architectural concepts on the protocol implementation in NCS. © 2010 IEEE.

关键词： Networked control systems

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Immune secondary response and clonal selection inspired optimizers

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Progress in Natural Science:Materials International 2009年第2期19卷 237-253页

作者： Maoguo Gong a,Licheng Jiao a,Lining Zhang a,Haifeng Du b a key laboratory of intelligent Perception and image Understanding of ministry of education of China,Institute of intelligent Information processing,Xidian University,Xi’an 710071,China b School of Public Policy and Administration,Xi’an Jiaotong University,Xi’an 710049,China [a]Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi’an 710071 China [b]School of Public Policy and Administration Xi’an Jiaotong University Xi’an 710049 China

The immune system’s ability to adapt its B cells to new types of antigen is powered by processes known as clonal selection and affinity maturation. When the body is exposed to the same antigen,immune system usually calls for a more rapid and larger response to the antigen,where B cells have the function of negative adjustment. Based on the clonal selection theory and the dynamic process of immune response,two novel artificial immune system algorithms,secondary response clonal programming algorithm (SRCPA) and secondary response clonal multi-objective algorithm (SRCMOA),are presented for solving single and multi-objective optimization problems,respectively. Clonal selection operator (CSO) and secondary response operator (SRO) are the main operators of SRCPA and SRCMOA. Inspired by the clonal selection theory,CSO reproduces individuals and selects their improved maturated progenies after the affinity mat-uration process. SRO copies certain antibodies to a secondary pool,whose members do not participate in CSO,but these antibodies could be activated by some external stimulations. The update of the secondary pool pays more attention to maintain the population diversity. On the one hand,decimal-string representation makes SRCPA more suitable for solving high-dimensional function optimiza-tion problems. Special mutation and recombination methods are adopted in SRCPA to simulate the somatic mutation and receptor edit-ing process. Compared with some existing evolutionary algorithms,such as OGA/Q,IEA,IMCPA,BGA and AEA,SRCPA is shown to be able to solve complex optimization problems,such as high-dimensional function optimizations,with better performance. On the other hand,SRCMOA combines the Pareto-strength based fitness assignment strategy,CSO and SRO to solve multi-objective optimization problems. The performance comparison between SRCMOA,NSGA-Ⅱ,SPEA,and PAES based on eight well-known test problems shows that SRCMOA has better performance in converging to approximate Pareto

关键词： Clonal selection Secondary response Artificial immune systems Evolutionary algorithms

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ANN-based control method implemented in a Voltage Source Converter for industrial Micro-Grid

ANN-based control method implemented in a Voltage Source Con...

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6th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2011

作者： Xu, Jinbang Wu, Zhizhuo Yang, Xuan Ye, Jie Shen, Anwen Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Department of Control Science and Technology Huazhong University of Science and Technology 430074 Wuhan China

ISBN: (纸本)9780769545141

With more and more attention on the grid current harmonic in recent years, many control schemes of the Pulse Width Modulation Voltage Source Converter (PWMVSC) have been investigated. Conventional PI controller has shown limitations such as sensitivity to load and system parameter variation. Even the stability of the system can be threatened under a large and sudden load change. In this paper, the practical situation of a VSC for industrial Micro Grid (MG) is considered and an Artificial neural network (ANN) based control method is employed to solve the problem. Meanwhile, an on-line parameter tuning algorithm is introduced for its advantage of self-tuning and system character identification. The proposed control scheme is verified through simulation based on SABER software. The simulation results have shown the advantage of the proposed method and the performance of the parameter tuning session. © 2011 IEEE.

关键词： Neural networks

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Graph-based scale-aware network for human parsing 1

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2nd Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2019

作者： Yang, Beibei Yu, Changqian Liu, Jiahui Gao, Changxin Sang, Nong Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9783030317232

ISBN: (纸本)9783030317225

Recent work has made considerable progress in exploring contextual information for human parsing with the Fully Convolutional Network framework. However, there still exist two challenges: (1) inherent relative relationships between parts;(2) scale variation of human parts. To tackle both problems, we propose a Graph-Based Scale-Aware Network for human parsing. First, we embed a Graph-Based Part Reasoning Layer into the backbone network to reason the relative relationship between human parts. Then we construct a Scale-Aware Context Embedding Layer, which consists of two branches to capture scale-specific contextual information, with different receptive fields and scale-specific supervisions. In addition, we adopt an edge supervision to further improve the performance. Extensive experimental evaluations demonstrate that the proposed model performs favorably against the state-of-the-art human parsing methods. More specifically, our algorithm achieves 53.32% (mIoU) on the LIP dataset. © Springer Nature Switzerland AG 2019.

关键词： Embeddings

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Formal specification and verification of reconfigurable protocol stack for networked control system

Formal specification and verification of reconfigurable prot...

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2010 International Conference on Networking, Sensing and control, ICNSC 2010

作者： Chen, Hui Zhou, Chunjie Huang, Xiongfeng Qing, Yuanqing Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Techonolgy Wuhan Hubei 430074 China

ISBN: (纸本)9781424464531

The protocol stack plays a critical role in determining the performance of Networked control System (NCS), which governs the communication activities and directly affects the communication Quality of Service (QoS). Full or partial reconfiguration of protocol stack offers both optimized communication service and system performance. This paper proposes a formal approach for the design and implementation of reconfiguration protocol stack based on Specification Description Language (SDL) for NCS. In Telelogic TAU environment, detail SDL models to support communication and reconfiguration functions of communication link layer, network transmission layer and application layer are discussed respectively. The MSC verification results validate the effective of our reconfiguration concepts on the protocol implementation for NCS. ©2010 IEEE.

关键词： Networked control systems

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