检索结果-内蒙古大学图书馆

Game-based peer-to-peer energy sharing management for a community of energy buildings

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2020年 123卷

作者： Cui, Shichang Xiao, Jiang-Wen Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Minist Educ Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China

Energy building techniques have gained significant attention for the potential to achieve local energy sustainability. Different from the research on individual energy management for zero energy buildings requiring sufficiently large renewable energy systems due to the mismatch of energy loads and generations, this paper investigates the coordinated energy management for a community of energy buildings with peer-to-peer energy sharing to promote community energy efficiency. Specifically, the energy buildings have controllable heating, ventilation and air conditioning (HVAC) units and renewable energy installations. In the coordinated energy management, in a peer-to-peer mode, the buildings determine their energy sharing profiles and related payments within the community while the sharing energy balance and payment balance are required to be satisfied. Since the buildings are self-interested, the problem with peer-to-peer energy sharing is modeled as a noncooperative game with global constraints. Then the existence of the game equilibrium is illustrated, and a distributed algorithm is proposed to seek the game equilibrium. A 6-building case and a 30-building case are carried out to verify the energy efficiency, economic benefits, and the scalability of the proposed peer-to-peer energy sharing management model.

关键词： Energy building Energy sharing Energy economics Noncooperative game Distributed optimization

来源：评论

学校读者我要写书评

暂无评论

T-TIME: Test-Time Information Maximization Ensemble for Plug-and-Play BCIs

arXiv

引用

arXiv 2024年

作者： Li, Siyang Wang, Ziwei Luo, Hanbin Ding, Lieyun 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 Wuhan430074 China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen China Henan Key Laboratory of Brain Science and Brain Computer Interface Technology School of Electrical and Information Engineering Zhengzhou University China School of Civil and Hydraulic Engineering Huazhong University of Science and Technology Wuhan430074 China

Objective: An electroencephalogram (EEG)-based brain-computer interface (BCI) enables direct communication between the human brain and a computer. Due to individual differences and non-stationarity of EEG signals, such BCIs usually require a subject-specific calibration session before each use, which is time-consuming and user-unfriendly. Transfer learning (TL) has been proposed to shorten or eliminate this calibration, but existing TL approaches mainly consider offline settings, where all unlabeled EEG trials from the new user are available. Methods: This paper proposes Test-Time Information Maximization Ensemble (T-TIME) to accommodate the most challenging online TL scenario, where unlabeled EEG data from the new user arrive in a stream, and immediate classification is performed. T-TIME initializes multiple classifiers from the aligned source data. When an unlabeled test EEG trial arrives, T-TIME first predicts its labels using ensemble learning, and then updates each classifier by conditional entropy minimization and adaptive marginal distribution regularization. Our code is publicized. Results: Extensive experiments on three public motor imagery based BCI datasets demonstrated that T-TIME outperformed about 20 classical and state-of-the-art TL approaches. Significance: To our knowledge, this is the first work on test time adaptation for calibration-free EEG-based BCIs, making plug-and-play BCIs possible. © 2024, CC BY.

关键词： Calibration

来源：评论

学校读者我要写书评

暂无评论

SCSQ-MDD: A Detection Approach for Multi-Style Strokes of Chinese Characters

SSRN

引用

SSRN 2023年

作者： Zhou, Tian Xie, Wu Zhang, Huimin Fan, Yong Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin China School of Computer Science and Information Security Guilin University of Electronic Technology Guilin China Key Lab of Education Blockchain and Intelligent Technology Ministry of Education Guangxi Normal University Guilin541004 China Guangxi Key Lab of Multi-Source Information Mining and Security Guangxi Normal University Guilin541004 China School of Mechanical and Electrical Engineering Guilin University of Electronic Science and Technology Guilin China

In the Chinese character writing task of the robotic arms, the stroke category and position information should be extracted by object detection. The detection algorithms based on predefined anchor frames have difficulty in resolving the differences among many different styles of Chinese character strokes. While the deformable detection transformer (deformable DETR) algorithms without predefined anchor frames result in some invalid sampling points having no contribution to the feature update of the current reference point due to the random sampling of sampling points in the deformable attention module. These processes cause the effectiveness of correlation calculations between reference points in Chinese strokes and their surrounding sampled points is limited. So that the speed of vector learning stroke features in the detection head is reduced. In view of this problem, a new detection method of multi-style strokes of Chinese characters via SCSQ-MDD (Simple Conditional Spatial Query Mask Deformable DETR) is proposed in this paper. Firstly, a mask prediction layer is jointly determined using the shallow feature map of the Chinese character image and the query vector of the transformer encoder, which is used to filter the points with actual contribution and resample the points without contribution, so that the randomness of correlation calculation among reference points is solved. Secondly, by separating the content query and spatial query of the transformer deocder, the content embedding and spatial embedding can be separately focused on when cross-attention computations are performed. Thus the dependence of the prediction task on the content embedding is relaxed and the training process is simplified. Finally, the detection model without predefined anchor frames based on deformable DETR called SCSQ-MDD is constructed using the mask mechanism and the simple conditional spatial query mechanism, and trained and validated on a multi-style Chinese character stroke dataset

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Learning feature fusion via an interpretation method for tumor segmentation on PET/CT

引用

APPLIED SOFT COMPUTING 2023年 148卷

作者： Kang, Susu Chen, Zhiyuan Li, Laquan Lu, Wei Qi, X. Sharon Tan, Shan Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Informat Proc & Intelligent Control Minist Educ China 1037 Luo Yu Rd Wuhan 430074 Hubei Peoples R China Chongqing Univ Posts & Telecommun Sch Sci 2 Chong Wen Rd Chongqing 400065 Peoples R China Mem Sloan Kettering Canc Ctr Dept Med Phys 1275 York Ave New York NY 10065 USA Univ Calif Los Angeles Sch Med Dept Radiat Oncol 10833 Le Conte Ave Los Angeles CA 90001 USA Huazhong Univ Sci & Technol Innovat Inst 1037 Luo Yu Rd Wuhan 430074 Hubei Peoples R China

Accurate tumor segmentation of multi-modality PET/CT images plays a vital role in computer-aided cancer diagnosis and treatment. It is crucial to rationally fuse the complementary information in multi-modality PET/CT segmentation. However, existing methods usually lack interpretability and fail to sufficiently identify and aggregate critical information from different modalities. In this study, we proposed a novel segmentation framework that incorporated an interpretation module into the multi-modality segmentation backbone. The interpretation module highlighted critical features from each modality based on their contributions to the segmentation performance. To provide explicit supervision for the interpretation module, we introduced a novel interpretation loss with two fusion schemes: strengthened fusion and perturbed fusion. The interpretation loss guided the interpretation module to focus on informative features, enhancing its effectiveness in generating meaningful interpretable masks. Under the guidance of the interpretation module, the proposed approach can fully exploit meaningful features from each modality, leading to better integration of multi-modality information and improved segmentation performance. Ablative and comparative experiments were conducted on two PET/CT tumor segmentation datasets. The proposed approach surpassed the baseline by 1.4 and 1.8 Dices on two datasets, respectively, indicating the improvement achieved by the interpretation method. Furthermore, the proposed approach outperformed the best comparison approach by 0.9 and 0.6 Dices on two datasets, respectively. In addition, visualization and perturbation experiments further illustrated the effectiveness of the interpretation method in highlighting critical features.

关键词： Tumor segmentation PET/CT images Feature fusion Network interpretation Deep learning

来源：评论

学校读者我要写书评

暂无评论

On the equivalence between the unbiased minimum-variance estimation and the infinity augmented Kalman filter

引用

INTERNATIONAL JOURNAL OF control 2020年第12期93卷 2995-3002页

作者： Ding, Bo Zhang, Tianping Fang, Huajing Yangzhou Univ Coll Informat Engn Dept Automat Yangzhou Jiangsu Peoples R China Huazhong Univ Sci & Technol Minist Educ Key Lab Image Proc & Intelligent Control Sch Automat Wuhan Peoples R China

In this paper, the augment Kalman filter (AKF) approach is discussed under the infinity condition. It is proved that the AKF in infinity condition is equivalent to the minimum-variance unbiased (MVU) estimation proposed in Gillijns & De Moor [(2007). Unbiased minimum-variance input and state estimation for linear discrete-time systems. Automatica, 43(1), 111-116]. This result can be regarded as a new contribution in the field of joint input and state estimation. Meanwhile, this result gives another way to estimate the state and unknown input simultaneously. Finally, the theoretical result is validated by simulations.

关键词： Infinity augment Kalman filter state estimation unknown input estimation linear discrete-time system

来源：评论

学校读者我要写书评

暂无评论

Transfer Learning for Brain-Computer Interfaces: A Euclidean Space Data Alignment Approach

引用

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING 2020年第2期67卷 399-410页

作者： He, He Wu, Dongrui Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Minist Educ Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China

Objective: This paper targets a major challenge in developing practical electroencephalogram (EEG)-based brain-computer interfaces (BCIs): how to cope with individual differences so that better learning performance can be obtained for a new subject, with minimum or even no subject-specific data? Methods: We propose a novel approach to align EEG trials from different subjects in the Euclidean space to make them more similar, and hence improve the learning performance for a new subject. Our approach has three desirable properties: first, it aligns the EEG trials directly in the Euclidean space, and any signal processing, feature extraction, and machine learning algorithms can then be applied to the aligned trials;second, its computational cost is very low;and third, it is unsupervised and does not need any label information from the new subject. Results: Both offline and simulated online experiments on motor imagery classification and event-related potential classification verified that our proposed approach outperformed a state-of-the-art Riemannian space data alignment approach, and several approaches without data alignment. Conclusion: The proposed Euclidean space EEG data alignment approach can greatly facilitate transfer learning in BCIs. Significance: Our proposed approach is effective, efficient, and easy to implement. It could be an essential pre-processing step for EEG-based BCIs.

关键词： Covariance matrices Electroencephalography Task analysis Signal processing Machine learning algorithms Microsoft Windows Brain-computer interfaces Brain-computer interface data alignment EEG Riemannian geometry transfer learning

来源：评论

学校读者我要写书评

暂无评论

Balancing control of neutral-point voltage for three-level T-type inverter based on hybrid variable virtual space vector

引用

IET POWER ELECTRONICS 2020年第4期13卷 744-750页

作者： Zhou, Jiancheng Cheng, Shanmei Hu, Zhenyu Liu, Jiang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Wuhan Peoples R China Wuhan Univ Sci & Technol Sch Informat Sci & Engn Wuhan Peoples R China

A three-level T-type inverter has higher efficiency and lower output voltage harmonics compared with the traditional two-level inverter. However, neutral-point voltage fluctuation and common-mode voltage (CMV) can negatively affect the performance of the three-level T-type inverter. This study proposes a novel hybrid variable virtual space vector ((HVSV)-S-2) strategy to mitigate this problem. Based on the virtual space vector scheme, new variable virtual small and medium vectors are reconstructed with the principle that the change of neutral-point charge of each virtual vector in a switching period is zero, and the adjustment factor is further added to the virtual vector to achieve the balance of the neutral-point voltage. At the same time, the vectors with a large CMV are eliminated to ensure that the CMV is minimised. Therefore, the (HVSV)-S-2 has excellent neutral-point voltage balance control capability and common-voltage suppression at both high- and low-modulation ratios. Theoretical analysis, simulations, and experimental results demonstrate the effectiveness and feasibility of the proposed strategy for full modulation ratios.

关键词： switching convertors PWM invertors voltage control two-level inverter neutral-point voltage fluctuation common-mode voltage CMV three-level T-type inverter virtual space vector scheme variable virtual small vectors medium vectors neutral-point charge virtual vector common-voltage suppression lower output voltage harmonics neutral-point voltage balance control capability hybrid variable virtual space vector

来源：评论

学校读者我要写书评

暂无评论

Joint Observer Gain and Input Design for Asymptotic Active Fault Diagnosis

arXiv

引用

arXiv 2024年

作者： Xu, Feng Wan, Yiming Wang, Ye Puig, Vicenç Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen518055 China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Ministry of Education China Wuhan430074 China Department of Electrical and Electronic Engineering The University of Melbourne ParkvilleVIC3010 Australia Universitat Politècnica de Catalunya Barcelona08028 Spain

This paper proposes a joint gain and input design method for observer-based asymptotic active fault diagnosis, which is based on a newly-defined notion named the excluding degree of the origin from a zonotope. Using the excluding degree, a quantitative specification is obtained to characterize the performance of set-based robust fault diagnosis. Furthermore, a single gain design method and a joint gain and input design method are proposed, respectively. This is the first work to achieve a joint observer gain and input design for set-based active fault diagnosis. Compared with the existing methods that design gains and input separately, the proposed joint gain and input design method has advantages to exploit the fault diagnosis potential of observer-based schemes. Finally, several examples are used to illustrate the effectiveness of the proposed methods. Copyright © 2024, The Authors. All rights reserved.

关键词： Design

来源：评论

学校读者我要写书评

暂无评论

Exploiting Distilled Learning for Deep Siamese Tracking 25

Exploiting Distilled Learning for Deep Siamese Tracking

引用

25th International Conference on Pattern Recognition (ICPR)

作者： Liu, Chengxin Cao, Zhiguo Li, Wei Xiao, Yang Du, Shuaiyuan Zhu, Angfan Huazhong Univ Sci & Technol Minist Educ Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Queen Mary Univ London London England

ISBN: (纸本)9781728188089

Existing deep siamese trackers are typically built on off-the-shelf CNN models for feature learning, with the demand for huge power consumption and memory storage. This limits current deep siamese trackers to be carried on resource-constrained devices like mobile phones, given factor that such a deployment normally requires cost-effective considerations. In this work, we address this issue by presenting a novel Distilled Learning Framework(DLF) for siamese tracking, which aims at learning tracking model with efficiency and high accuracy. Specifically, we propose two simple yet effective knowledge distillation strategies, denote as point-wise distillation and pair-wise distillation, which are designed for transferring knowledge from a more discriminative teacher tracker into a compact student tracker. In this way, cost-effective and high performance tracking could be achieved. Extensive experiments on several tracking benchmarks demonstrate the effectiveness of our proposed method.

关键词： Distillation

来源：评论

学校读者我要写书评

暂无评论

Basic theorem and global exponential stability of differential-algebraic neural networks with delay

引用

NEURAL NETWORKS 2021年 140卷 336-343页

作者： Chen, Jiejie Chen, Boshan Zeng, Zhigang Hubei Normal Univ Coll Comp Sci & Informat Engn Huangshi 435002 Hubei Peoples R China Hubei Normal Univ Coll Math & Stat Huangshi 435002 Hubei Peoples R China Huazhong Univ Sci & Technol Sch Automat Wuhan 430074 Peoples R China Educ Minist China Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China

A differential-algebraic neural network (DANN) with delay (DDANN) is proposed. Firstly, the global existence and uniqueness theorems are established for a DDANN, respectively. Next, a new differential-algebraic inequality is established. Then, a theorem on global exponential stability of DDANN is shown by using this inequality. As an application of DDANN, a very concise criterion on global exponential stability for a neutral-type neural network is given by using DDANNs. Finally, two examples are given to illustrate the theoretical results. (C) 2021 Published by Elsevier Ltd.

关键词： Global existence and uniqueness theorem Global exponential stability Differential-algebraic neural networks Singular neural networks Neutral-type neural networks

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：