检索结果-内蒙古大学图书馆

Neuromorphic Computing (ICNC), International Conference on

作者： Ningye Jiang Mingxuan Jiang Zhigang Zeng School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Huazhong University of Science and Technology Wuhan China

Memristor crossbar array is considered as a promising circuit module for accelerating neural networks. Because the memristor is tunable and multi-state, it is important to design applicable Read-Write (RW) circuit for driving memristor crossbar array. In this paper, a novel RW circuit based on analog circuits is proposed for tuning memristors in high-dimensional array parallelly, which is scalable and low-overhead. The standalone RW circuit schematic is presented for reading/writing single memristor and verified in circuit simulation. Then, we extend and apply this circuit into a two-dimensional memristor crossbar array. The performance of memristor crossbar array controlled by designed RW circuits is verified via the simulations under various machine learning datasets. The comparison with related works is presented, which demonstrates the advantages of the proposed RW circuit regarding overhead and anti-error.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Global Optimization: A Distributed Compensation Algorithm and its Convergence Analysis

引用

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2021年第4期51卷 2355-2369页

作者： Lin, Wen-Ting Wang, Yan-Wu Li, Chaojie Xiao, Jiang-Wen Huazhong Univ Sci & Technol Sch Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Minist Educ Wuhan 430074 Peoples R China Aliexpress Alibaba Grp Hangzhou 311100 Peoples R China

This paper introduces a distributed compensation approach for the global optimization with separable objective functions and coupled constraints. By employing compensation variables, the global optimization problem can be solved without the information exchange of coupled constraints. The convergence analysis of the proposed algorithm is presented with the convergence condition through which a diminishing step-size with an upper bound can be determined. The convergence rate can be achieved at O(lnT/root T). Moreover, the equilibrium of this algorithm is proved to converge at the optimal solution of the global optimization problem. The effectiveness and the practicability of the proposed algorithm is demonstrated by the parameter optimization problem in smart building.

关键词： Compensation approach coupled constraints distributed optimization global optimal

来源：评论

学校读者我要写书评

暂无评论

A Novel Hybrid Algorithm for the Forward Kinematics Problem of 6 DOF Based on Neural Networks

引用

SENSORS 2022年第14期22卷 5318-5318页

作者： Zhu, Huizhi Xu, Wenxia Yu, Baocheng Ding, Feng Cheng, Lei Huang, Jian Wuhan Inst Technol Sch Comp Sci & Engn Artificial Intelligence Engn Res Ctr Intelligent Prod Line Equipment Hube Wuhan 430205 Peoples R China South Cent Minzu Univ Sch Comp Sci Wuhan 430074 Peoples R China Wuhan Univ Sci & Technol Sch Informat Sci & Engn Wuhan 430081 Peoples R China Huazhong Univ Sci & Technol Sch Automat Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China

The closed kinematic structure of Gough-Stewart platforms causes the kinematic control problem, particularly forward kinematics. In the traditional hybrid algorithm (backpropagation neural network and Newton-Raphson), it is difficult for the neural network part to train different datasets, causing training errors. Moreover, the Newton-Raphson method is unable to operate on a singular Jacobian matrix. In this study, in order to solve the forward kinematics problem of Gough-Stewart platforms, a new hybrid algorithm is proposed based on the combination of an artificial bee colony (ABC)-optimized BP neural network (ABC-BPNN) and a numerical algorithm. ABC greatly improves the prediction ability of neural networks and can provide a superb initial value to numerical algorithms. In the design of numerical algorithms, a modification of Newton's method (QMn-M) is introduced to solve the problem that the traditional algorithm model cannot be solved when it is trapped in singular matrix. Results show that the maximal improvement in ABC-BPNN error optimization was 46.3%, while the RMSE index decreased by 42.1%. Experiments showed the feasibility of QMn-M in solving singular matrix data, while the percentage improvement in performance for the average number of iterations and required time was 14.4% and 13.9%, respectively.

关键词： Gough-Stewart forward kinematics problem ABC-BPNN Newton's method

来源：评论

学校读者我要写书评

暂无评论

Quantized event-triggered communication based multi-agent system for distributed resource allocation optimization q

引用

INFORMATION SCIENCES 2021年 577卷 336-352页

作者： Li, Kaixuan Liu, Qingshan Zeng, Zhigang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Minist Educ Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Southeast Univ Sch Math Nanjing 210096 Peoples R China Jiangsu Prov Key Lab Networked Collect Intelligen Nanjing 210096 Peoples R China

This paper investigates a multi-agent system with quantized event-triggered communication mechanisms to reduce the communication expenditure. The event-triggered communication mechanism is proposed to reduce the utilization of communication bandwidth, which lowers the communication expenditure in communication frequency. The quantized communication mechanism quantizes the communication information in the multi-agent system with limited communication capacity. First, a quantized periodic communication mechanism system is proposed, which provides a lower bound of the communication interval for the quantized event-triggered communication system to avoid the Zeno behavior. Then the system with quantized event-triggered communication is proved to be convergent to an optimal solution of distributed constraint optimization. With the quantized communication mechanism, the system can reduce the communication cost in the frequency of communication and the amount of transmission data. The proposed method has a tradeoff between energy saving and precision. Finally, the simulation results with comparisons verify the convergence of the system and exhibit the accuracy with different quantizer densities. (c) 2021 Elsevier Inc. All rights reserved.

关键词： Resource allocation Multi-agent system Distributed optimization Quantized event-triggered communication

来源：评论

学校读者我要写书评

暂无评论

Distributed Resource Allocation via Accelerated Saddle Point Dynamics

引用

IEEE/CAA Journal of Automatica Sinica 2021年第9期8卷 1588-1599页

作者： Wen-Ting Lin Yan-Wu Wang Chaojie Li Xinghuo Yu School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074 Key Laboratory of Image Processing and Intelligent Control Ministry of EducationHuazhong University of Science and TechnologyWuhan 430074China School of Electrical Engineering and Telecommunications University of New South WalesSydney NSW 2052Australia School of Engineering Royal Melbourne Institute of Technology(RMIT University)Melbourne VIC 3000Australia

In this paper,accelerated saddle point dynamics is proposed for distributed resource allocation over a multi-agent network,which enables a hyper-exponential convergence ***,an inertial fast-slow dynamical system with vanishing damping is introduced,based on which the distributed saddle point algorithm is *** dual variables are updated in two time scales,i.e.,the fast manifold and the slow *** the fast manifold,the consensus of the Lagrangian multipliers and the tracking of the constraints are pursued by the consensus *** the slow manifold,the updating of the Lagrangian multipliers is accelerated by inertial ***-exponential stability is defined to characterize a faster convergence of our proposed algorithm in comparison with conventional primal-dual algorithms for distributed resource *** simulation of the application in the energy dispatch problem verifies the result,which demonstrates the fast convergence of the proposed saddle point dynamics.

关键词： Accelerated saddle point dynamic distributed resource allocation hyper-exponential stability power dispatch

来源：评论

学校读者我要写书评

暂无评论

MindEye-OmniAssist: A Gaze-Driven LLM-Enhanced Assistive Robot System for Implicit Intention Recognition and Task Execution

arXiv

引用

arXiv 2025年

作者： Zhang, Zejia Yang, Bo Chen, Xinxing Shi, Weizhuang Wang, Haoyuan Luo, Wei Huang, Jian Hubei Key Laboratory of Brain-Inspired Intelligent Systems Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China State key laboratory of intelligent vehicle safety technology chongqing changan automobile co ltd Chongqing400023 China Science and technology innovation center China ship development and design centre Wuhan430060 China

A promising effective human-robot interaction in assistive robotic systems is gaze-based control. However, current gaze-based assistive systems mainly help users with basic grasping actions, offering limited support. Moreover, the restricted intent recognition capability constrains the assistive system’s ability to provide diverse assistance functions. In this paper, we propose an open implicit intention recognition framework powered by Large Language Model (LLM) and Vision Foundation Model (VFM), which can process gaze input and recognize user intents that are not confined to predefined or specific scenarios. Furthermore, we implement a gaze-driven LLM-enhanced assistive robot system (MindEye-OmniAssist) that recognizes user’s intentions through gaze and assists in completing task. To achieve this, the system utilizes open vocabulary object detector, intention recognition network and LLM to infer their full intentions. By integrating eye movement feedback and LLM, it generates action sequences to assist the user in completing tasks. Real-world experiments have been conducted for assistive tasks, and the system achieved an overall success rate of 41/55 across various undefined tasks. Preliminary results show that the proposed method holds the potential to provide a more user-friendly human-computer interaction interface and significantly enhance the versatility and effectiveness of assistive systems by supporting more complex and diverse task. Copyright © 2025, The Authors. All rights reserved.

关键词： Eye movements

来源：评论

学校读者我要写书评

暂无评论

Watch the Speakers: A Hybrid Continuous Attribution Network for Emotion Recognition in Conversation With Emotion Disentanglement 35

Watch the Speakers: A Hybrid Continuous Attribution Network ...

引用

35th IEEE International Conference on Tools with Artificial Intelligence (ICTAI)

作者： Lei, Shanglin Wang, Xiaoping Dong, Guanting Li, Jiang Liu, Yingjian Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Key Lab Image Proc & Intelligent Control Educ Min Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol HUST Inst Artificial Intelligence Wuhan 430074 Peoples R China Beijing Univ Posts & Telecommun Sch Artificial Intelligence Beijing 100876 Peoples R China

ISBN: (纸本)9798350342734

Emotion Recognition in Conversation (ERC) has attracted widespread attention in the natural language processing field due to its enormous potential for practical applications. Existing ERC methods face challenges in achieving generalization to diverse scenarios due to insufficient modeling of context, ambiguous capture of dialogue relationships and overfitting in speaker modeling. In this work, we present a Hybrid Continuous Attributive Network (HCAN) to address these issues in the perspective of emotional continuation and emotional attribution. Specifically, HCAN adopts a hybrid recurrent and attention-based module to model global emotion continuity. Then a novel Emotional Attribution Encoding (EAE) is proposed to model intra- and inter-emotional attribution for each utterance. Moreover, aiming to enhance the robustness of the model in speaker modeling and improve its performance in different scenarios, A comprehensive loss function emotional cognitive loss L-EC is proposed to alleviate emotional drift and overcome the overfitting of the model to speaker modeling. Our model achieves state-of-the-art performance on three datasets, demonstrating the superiority of our work. Another extensive comparative experiments and ablation studies on three benchmarks are conducted to provided evidence to support the efficacy of each module. Further exploration of generalization ability experiments shows the plugand-play nature of the EAE module in our method.

关键词： Natural language processing emotion recognition in conversation context modeling dialogue relationship

来源：评论

学校读者我要写书评

暂无评论

Design and Optimization of Liquid State Machine for Handwritten Digit Recognition

Design and Optimization of Liquid State Machine for Handwrit...

引用

2022 Workshop on Electronics Communication Engineering

作者： Hou, Aihu Liu, Jie Zhou, Kaibo Zhou, Wenli School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China School of Civil and Hydraulic Engineering Huazhong University of Science and Technology Wuhan430074 China Hubei Key Laboratory of Digital River Basin Science and Technology Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Ministry of Education Wuhan430074 China School of Optical and Electronic information Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781510666634

The most commonly used implementation of handwritten digit recognition based on convolutional neural networks requires equipment with high computing power, which is not suitable for edge devices. Recently, spiking neural network (SNN) has received more attentions due to its low power consumption and real-time performance, but training SNN is very difficult. As a special SNN, liquid state machine (LSM) has the advantages of simple structure and easy training, so it is very suitable for handwritten digit recognition on edge devices. But it has no advantage in recognition accuracy. In order to improve the performance of LSM, its reservoir needs to be optimized. In this paper, an efficient local optimization strategy is proposed, improving the recognition accuracy of LSM by 11.8% with less the training time. In order to reduce the runtime, auto-encoder and feature screening are used to compress the input handwritten digit image. After feature compression, the input storage is reduced by 57%, and the runtime is reduced by 30%. This work provides an effective way to realize handwritten digit recognition on the edge devices. © 2023 SPIE.

关键词： Computing power

来源：评论

学校读者我要写书评

暂无评论

Adversarial attacks and defenses in physiological computing:a systematic review

引用

National Science Open 2023年第1期2卷 62-90页

作者： Dongrui Wu Jiaxin Xu Weili Fang Yi Zhang Liuqing Yang Xiaodong Xu Hanbin Luo Xiang Yu Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China Zhejiang Lab Hangzhou 311121China School of Civil and Hydraulic Engineering Huazhong University of Science and TechnologyWuhan 430074China College of Public Administration Huazhong University of Science and TechnologyWuhan 430074China Electrical Engineering and Computer Science Department University of MichiganAnn Arbor MI 48109USA School of Management and Sino-European Institute for Intellectual Property Huazhong University of Science and TechnologyWuhan 430074China

Physiological computing uses human physiological data as system inputs in real *** includes,or significantly overlaps with,brain-computer interfaces,affective computing,adaptive automation,health informatics,and physiological signal based *** computing increases the communication bandwidth from the user to the computer,but is also subject to various types of adversarial attacks,in which the attacker deliberately manipulates the training and/or test examples to hijack the machine learning algorithm output,leading to possible user confusion,frustration,injury,or even ***,the vulnerability of physiological computing systems has not been paid enough attention to,and there does not exist a comprehensive review on adversarial attacks to *** study fills this gap,by providing a systematic review on the main research areas of physiological computing,different types of adversarial attacks and their applications to physiological computing,and the corresponding defense *** hope this review will attract more research interests on the vulnerability of physiological computing systems,and more importantly,defense strategies to make them more secure.

关键词： physiological computing brain-computer interfaces health informatics biometrics machine learning adversarial attack

来源：评论

学校读者我要写书评

暂无评论

Bayesian Learning-Based Multi-Objective Distribution Power Network Reconfiguration

引用

IEEE TRANSACTIONS ON SMART GRID 2021年第2期12卷 1174-1184页

作者： Zhong, Tianwei Zhang, Hai-Tao Li, Yuanzheng Liu, Lan Lu, Renzhi Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Peoples R China Cent China Normal Univ Natl Engn Lab Educ Big Data Wuhan 430079 Peoples R China

This article proposes a scheme aiming at solving the reconfiguration problem of distribution power network (DPN) with high wind power penetrations. The virtue of the presented scheme lies in balancing the voltage stability and the absorption rate of wind energy. First, the DPN reconfiguration is formulated as a multi-objective optimization problem, where a curtailment strategy is introduced with the assistance of the secure operations of DPN. Thereby, the absorption rate of the generated wind power is maximized and voltage stability level is improved as well. Meanwhile, a modified multi-objective Bayesian learning-based evolutionary algorithm is applied to yield a Pareto front, which is a tradeoff between absorption rate and voltage stability. Afterwards, A technique for order preference by similarity to an ideal solution (TOPSIS) is adopted to determine the dispatching solution by similarity to an ideal solution. Finally, numerical case studies are conducted on a modified IEEE-33 bus system to verify the effectiveness of the proposed scheme.

关键词： Wind power generation Absorption Power system stability Optimization Stability analysis Stochastic processes Bayes methods Wind power distribution power network reconfiguration multi-objective optimization Bayesian learning%

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：