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Modeling the Temporal Dynamics of EEG Signals in Selective Listening

IEEE Transactions on Consumer Electronics 2025年

作者： Cai, Siqi Zhang, Ran Zhu, Hongxu Li, Haizhou National University of Singapore Department of Electrical and Computer Engineering Singapore Singapore South China University of Technology Shien-Ming Wu School of Intelligent Engineering China Fano Hong Kong Hong Kong The Chinese University of Hon g Kong Shenzhen Research Institute of Big Data School of Data Science Shenzhen518172 China University of Bremen Machine Listening Lab Bremen28359 Germany

Human brain possesses an extraordinary ability to attend to a specific sound source in a multi-talk, noisy environment such as a cocktail party. Auditory attention detection (AAD) aims to automatically identify such attentive neural activity from brain signals, such as electroencephalography (EEG). Given the dynamic and nonlinear nature of EEG signals, we propose a spiking long short-term memory (LSTM) network to capture the temporal features from EEG data. Additionally, we introduce a spiking temporal attention mechanism that dynamically assigns differentiated weights, thereby enhancing the representation of EEG features. We evaluate our proposed spiking temporal LSTM model, named ST-LSTM, on a widely used AAD dataset through a wide range of experiments. The experiments demonstrate that ST-LSTM outperforms other competing models, especially in low-latency settings. Moreover, with low power consumption, ST-LSTM offers a practical solution for edge computing implementations such as neuro-steered hearing aids, and other portable brain-computer interfaces. © 1975-2011 IEEE.

关键词： Hearing aids

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MICkNN:Multi-Instance Covering kNN Algorithm

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Tsinghua science and technology 2013年第4期18卷 360-368页

作者： Shu Zhao Chen Rui Yanping Zhang Department of Computer Science and Technology and Key Lab of Intelligent Computing and Signal Processing Anhui University

Mining from ambiguous data is very important in data mining. This paper discusses one of the tasks for mining from ambiguous data known as multi-instance problem. In multi-instance problem, each pattern is a labeled bag that consists of a number of unlabeled instances. A bag is negative if all instances in it are negative. A bag is positive if it has at least one positive instance. Because the instances in the positive bag are not labeled, each positive bag is an ambiguous. The mining aim is to classify unseen bags. The main idea of existing multi-instance algorithms is to find true positive instances in positive bags and convert the multi-instance problem to the supervised problem, and get the labels of test bags according to predict the labels of unknown instances. In this paper, we aim at mining the multi-instance data from another point of view, i.e., excluding the false positive instances in positive bags and predicting the label of an entire unknown bag. We propose an algorithm called Multi-Instance Covering kNN （MICkNN） for mining from multi-instance data. Briefly, constructive covering algorithm is utilized to restructure the structure of the original multi-instance data at first. Then, the kNN algorithm is applied to discriminate the false positive instances. In the test stage, we label the tested bag directly according to the similarity between the unseen bag and sphere neighbors obtained from last two steps. Experimental results demonstrate the proposed algorithm is competitive with most of the state-of-the-art multi-instance methods both in classification accuracy and running time.

关键词： mining ambiguous data multi-instance classification constructive covering algorithm kNN algorithm

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Constraints-Aware Scheduling for Transactional Services Composition

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Journal of computer science & technology 2009年第4期24卷 638-651页

作者：刘安刘海李青黄刘生肖明军 Department of Computer Science and Technology University of Science and Technology of China Joint Research Lab of Excellence CityU-USTC Advanced Research Institute Department of Computer Science City University of Hong Kong Joint Research Lab of Excellence City U-USTC Advanced Research Institute CCF IEEE

Composite Web services need transactional support to guarantee their consistent and reliable execution. Due to the long running and inter-organizational characteristics of Web services, current approaches for transactional Web setvices composition adopt compensation mechanism to maintain atomicity. A common assumption is that a compensation operation can be applied at any time with no cost. However, compensation operations are typically associated with temporal and cost constraints, which make compensation mechanism problematic in this new environment. To address this problem, we distinguish two types of scheduling for transactional Web services composition： time aware scheduling and cost aware scheduling. We devise several algorithms for scheduling, which can ensure the atomicity of composite services when compensation operations have temporal constraints, and assist composite services to maintain atomicity with minimum compensation cost when compensation operations have cost constraints. We benchmark our algorithms by simulations and the results show that our algorithm decreases the compensation cost and in turn improves the QoS of transactional services composition.

关键词： compensation cost service composition time transaction

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A layered workflow knowledge Grid/P2P architecture and its models for future generation workflow systems

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FUTURE GENERATION computer SYSTEMS-THE INTERNATIONAL JOURNAL OF Escience 2007年第3期23卷 304-316页

作者： Kim, Kwang-Hoon Collaboration Technology Research Lab. Department of Computer Science Kyonggi University South Korea

This paper addresses the scalability issue on workflow systems using the knowledge Grid/P2P computing environment. As a feasible solution for the scalability issue, we design a Layered Workflow Knowledge Grid/P2P Architecture. The architecture is based upon a conceptual and generic framework that considers various perspectives for creating workflow knowledge Grid/P2P architectures. In order to show how the architecture is applicable in making up a future generation workflow system, we propose three types of workflow knowledge models and a physical architecture that is possibly configurable from the layered workflow knowledge Grid/P2P architecture. That is, the architecture has a 3-layered hierarchical configuration-procedure-layer, role-layer, and actor-layer - and the three workflow knowledge models-ICN-based model, role-based model, and actor-based model - are the workflow knowledge representations on Grid/P2P nodes in the corresponding layers, respectively. In particular, the most critical rationale of this paper is based on the fact that the nature of the knowledge Grid/P2P computing environment ought to be fitted very well into building a platform for future generation workflow systems characterized by maximally parallel and very large scale workflow procedures that are frequently observed in very large scale enterprizes. And we strongly believe that the rationale must be acceptable. Conclusively, the architecture and the models proposed in this paper shall be useful for not only maximizing the usability of computing facilities in the enterprize but also appropriately handling the scalability issue of its underlined future generation workflow management system in order to cope with massively parallel and very large scale workflow applications. (c) 2006 Elsevier B.V. All rights reserved.

关键词： layered workflow knowledge Grid/P2P architectures workflow knowledge models knowledge Grid/P2P future generation workflow systems massively parallel and very large-scale workflows

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Hierarchical Covering Algorithm

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Tsinghua science and technology 2014年第1期19卷 76-81页

作者： Jie Chen Shu Zhao Yanping Zhang Department of Computer Science and Technology and Key Lab of Intelligent Computing and Signal Processing Anhui University

The concept of deep learning has been applied to many domains, but the definition of a suitable problem depth has not been sufficiently explored. In this study, we propose a new Hierarchical Covering Algorithm （HCA） method to determine the levels of a hierarchical structure based on the Covering Algorithm （CA）. The CA constructs neural networks based on samples＇ own characteristics, and can effectively handle multi-category classification and large-scale data. Further, we abstract characters based on the CA to automatically embody the feature of a deep structure. We apply CA to construct hidden nodes at the lower level, and define a fuzzy equivalence relation R on upper spaces to form a hierarchical architecture based on fuzzy quotient space theory. The covering tree naturally becomes from R. HCA experiments performed on MNIST dataset show that the covering tree embodies the deep architecture of the problem, and the effects of a deep structure are shown to be better than having a single level.

关键词： deep architecture hierarchy fuzzy equivalence relation covering tree MNIST dataset

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Robust Adaptive Neural Control of a Class of MIMO Nonlinear Systems

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Tsinghua science and technology 2007年第1期12卷 14-21页

作者：胡亭亮朱纪洪孙增圻 State Key Lab of Intelligent Technology and Systems Department of Computer Science and Technology Tsinghua University

In this paper we present a robust adaptive control for a class of uncertain continuous time multiple input multiple output （MIMO） nonlinear systems. Multiple multi-layer neural networks are employed to approximate the uncertainty of the nonlinear functions, and robustifying control terms are used to compensate for approximation errors. All parameter adaptive laws and robustifying control terms are derived based on Lyapunov stability analysis so that, under appropriate assumptions, semi-global stability of the closed-loop system is guaranteed, and the tracking error asymptotically converges to zero. Simulations performed on a two-link robot manipulator illustrate the approach and its performance.

关键词： direct adaptive control neural networks nonlinear system stability

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DRL-Based Optimization for AoI and Energy Consumption in C-V2X Enabled IoV

IEEE Transactions on Green Communications and Networking

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IEEE Transactions on Green Communications and Networking 2025年

作者： Zhang, Zheng Wu, Qiong Fan, Pingyi Cheng, Nan Chen, Wen Letaief, Khaled B. Jiangnan University School of Internet of Things Engineering Wuxi214122 China Tsinghua University Beijing National Research Center for Information Science and Technology Department of Electronic Engineering State Key laboratory of Space Network and Communications Tsinghua University Beijing100084 China Xidian University State Key Lab. of ISN School of Telecom-munications Engineering Xi'an710071 China Shanghai Jiao Tong University Department of Electronic Engineering Shanghai200240 China Department of Electrical and Computer Engineer-ing Hong Kong

To address communication latency issues, the Third Generation Partnership Project (3GPP) has defined Cellular-Vehicle to Everything (C-V2X) technology, which includes Vehicle-to-Vehicle (V2V) communication for direct vehicle-to-vehicle communication. However, this method requires vehicles to autonomously select communication resources based on the Semi-Persistent Scheduling (SPS) protocol, which may lead to collisions due to different vehicles sharing the same communication resources, thereby affecting communication effectiveness. Non-Orthogonal Multiple Access (NOMA) is considered a potential solution for handling large-scale vehicle communication, as it can enhance the Signal-to-Interference-plus-Noise Ratio (SINR) by employing Successive Interference Cancellation (SIC), thereby reducing the negative impact of communication collisions. When evaluating vehicle communication performance, traditional metrics such as reliability and transmission delay present certain contradictions. Introducing the new metric Age of Information (AoI) provides a more comprehensive evaluation of communication system. Additionally, to ensure service quality, user terminals need to possess high computational capabilities, which may lead to increased energy consumption, necessitating a trade-off between communication energy consumption and effectiveness. Given the complexity and dynamics of communication systems, Deep Reinforcement Learning (DRL) serves as an intelligent learning method capable of learning optimal strategies in dynamic environments. Therefore, this paper analyzes the effects of multi-priority queues and NOMA on AoI in the C-V2X vehicular communication system and proposes an energy consumption and AoI optimization method based on DRL. Finally, through comparative simulations with baseline methods, the proposed approach demonstrates its advances in terms of energy consumption and AoI. © 2017 IEEE.

关键词： Deep reinforcement learning

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A refinement calculus for specifications in Hennessy-Milner logic with recursion

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Formal Aspects of Computing 1989年第1期1卷 242-272页

作者： Holmström, Sören Programming Methodology Group Department of Computer Science Chalmers University of Technology Göteborg S-412 96 Sweden

This paper is about specification and verification of processes, modelled as CCS-agents. We show, by means of examples that Hennessy-Milner Logic (HML) with recursion is a suitable language for expressing implicit or partial specifications. By extending this specification language with refinement operators, i.e. operators that describe the internal structure of a system, we obtain a calculus for stepwise refinement of agents from a specification in HML to a realisation in CCS. The method is demonstrated by proving the alternating-bit protocol under weak assumptions about the unreliable media. © 1989 BCS.

关键词： CCS Concurrency Hennessy-Milner logic Specification languages Stepwise refinement Verification

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Design and analysis of a network coding algorithm for ad hoc networks

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Journal of Central South University 2015年第4期22卷 1358-1365页

作者：王远徐华贾培发 State Key Lab of Intelligent Technology & Systems (Tsinghua University) Tsinghua National Lab for Information Science & Technology (Tsinghua University) Department of Computer Science & Technology Tsinghua University Unit 95899 of Air Force of CPLA

Network coding is proved to have advantages in both wireline and wireless networks. Especially, appropriate network coding schemes are programmed for underlined networks. Considering the feature of strong node mobility in aviation communication networks, a hop-by-hop network coding algorithm based on ad hoc networks was proposed. Compared with COPE-like network coding algorithms, the proposed algorithm does not require overhearing from other nodes, which meets confidentiality requirements of aviation communication networks. Meanwhile, it does save resource consumption and promise less processing delay. To analyze the performance of the network coding algorithm in scalable networks with different traffic models, a typical network was built in a network simulator, through which receiving accuracy rate and receiving delay were both *** simulation results indicate that, by virtue of network coding, the proposed algorithm works well and improves performance significantly. More specifically, it has better performance in enhancing receiving accuracy rate and reducing receiving delay, as compared with any of the traditional networks without coding. It was applied to both symmetric and asymmetric traffic flows and, in particular, it achieves much better performance when the network scale becomes larger. Therefore, this algorithm has great potentials in large-scale multi-hop aviation communication networks.

关键词： ad hoc network network coding algorithm aviation communication network

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Collaborative Network Security in Multi-Tenant Data Center for Cloud Computing

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Tsinghua science and technology 2014年第1期19卷 82-94页

作者： Zhen Chen Wenyu Dong Hang Li Peng Zhang Xinming Chen Junwei Cao Research Institute of Information Technology and Tsinghua National Lab for Information Science and Technology Tsinghua University Department of Computer Science and Technology Tsinghua University Department of Computer Science and Technology PLA Univ. of Info. & Eng. Department of Electronic and Information Engineering Xi’an Jiaotong University Department of Electrical and Computer Engineering University of Massachusetts

A data center is an infrastructure that supports Internet service. Cloud comput the face of the Internet service infrastructure, enabling even small organizations to quickly ng is rapidly changing build Web and mobile applications for millions of users by taking advantage of the scale and flexibility of shared physical infrastructures provided by cloud computing. In this scenario, multiple tenants save their data and applications in shared data centers, blurring the network boundaries between each tenant in the cloud. In addition, different tenants have different security requirements, while different security policies are necessary for different tenants. Network virtualization is used to meet a diverse set of tenant-specific requirements with the underlying physical network enabling multi-tenant datacenters to automatically address a large and diverse set of tenants requirements. In this paper, we propose the system implementation of vCNSMS, a collaborative network security prototype system used n a multi-tenant data center. We demonstrate vCNSMS with a centralized collaborative scheme and deep packet nspection with an open source UTM system. A security level based protection policy is proposed for simplifying the security rule management for vCNSMS. Different security levels have different packet inspection schemes and are enforced with different security plugins. A smart packet verdict scheme is also integrated into vCNSMS for ntelligence flow processing to protect from possible network attacks inside a data center network

关键词： data center network network security software defined network collaborative network security multi- tenant network virtualization intelligent flow processing cloud computing

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