检索结果-内蒙古大学图书馆

Cross-Modal Haptic Compression Inspired by Embodied AI for Haptic communications

IEEE Transactions on Multimedia 2025年

作者： Lu, Hang Tan, Xinmeng Chen, Mingkai Zhang, Zhe Zhang, Xuguang Chen, Jianxin Wei, Xin Zhao, Tiesong Nanjing University of Posts and Telecommunications Key Laboratory of Broadband Wireless Communication and Sensor Network Technology China Fuzhou University Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information College of Physics and Information Engineering Fuzhou350108 China Fuzhou University Fujian Science & Technology Innovation Laboratory for Optoelectronic Information Fuzhou350108 China

Haptic data compression has gradually become a key issue for emerging real-time haptic communications in Tactile Internet (TI). However, it is challenging to achieve a tradeoff between high perceptual quality and compression ratio in haptic data compression scheme. Inspired by the perspective of embodied AI, we propose a cross-modal haptic compression scheme for haptic communications to improve the perception quality on TI devices in this paper. Since multimodal fusion is routinely employed to improve the ability of system in cognition, we assume that haptic codec is guided by visual semantics to optimize parameter settings in the coding process. We first design a multi-dimensional tactile feature fusion network (MTFFN) relying on multi-head attention mechanism. The MTFFN extracts the multi-dimensional features from the material surface and maps them to infer the coding parameters. Secondly, we provide second-order difference and linear interpolation to establish an criterion for the determination of optimal codec parameters, which are customized by the material categories so as to give high robustness. Finally, the simulation results reveal that our compression scheme can efficiently make a personalized codec procedure for different materials, obtaining more than 17% improvement in terms of compression ratio with high perceptual quality at the same time. © 2025 IEEE.

关键词： Data compression ratio

来源：评论

学校读者我要写书评

暂无评论

Progressive Masking Oriented Self-Taught Learning for Occluded Facial Expression Recognition

引用

IEEE Transactions on Affective Computing 2025年

作者： Kang, Bin Wang, Shuangshuang Wang, Zongyu Li, Xin Dou, Haie Wang, Lei Xia, Zhijie College of Internet of Things Nanjing University of Posts and Telecommunications Nanjing China Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Ministry of Education Nanjing China School of Mechanical Engineering Southeast University Nanjing China

Self-taught learning (STL) is a promising solution that reduces the performance gap between weakly supervised and fully supervised learning for easily accessible, label-free images. The success of traditional STL solutions relies on the assumption that the target appearance is completely visible and well-defined. In real-world facial expression recognition scenarios, however, saliency regions are often partially occluded, which significantly hampers the generalization capability of STL methods. Nevertheless, few studies have investigated the impact of occlusion on STL. In this paper, we propose an interweaved autoencoder network for weakly supervised facial expression recognition in occlusion scenarios. The key innovation of our network lies in the Residual Connection Union (RCU) blocks that can integrate the Convolutional Neural network (CNN) and Transformer layers into a multi-scale structure. The RCU enables a progressive masking strategy to accurately identify and focus on contributive yet often overlooked image patches by analyzing the relationships among region-level target representations. In addition, we introduce a self-knowledge distillation module for the effective training of the proposed autoencoder network. Extensive experiments are conducted on four public datasets to demonstrate the superiority of our method over related works. © 2010-2012 IEEE All rights reserved.

关键词： Self-supervised learning

来源：评论

学校读者我要写书评

暂无评论

Improved finite-size analysis for measurement-device-independent quantum digital signature

arXiv

引用

arXiv 2025年

作者： Zhu, Jia-Li Zhang, Chun-Hui Wang, Yue-Ying Wang, Qin Institute of quantum information and technology Nanjing University of Posts and Telecommunications Nanjing210003 China "Broadband Wireless Communication and Sensor Network Technology" Key Lab of Ministry of Education NUPT Nanjing210003 China "Telecommunication and Networks" National Engineering Research Center NUPT Nanjing210003 China

Quantum digital signatures (QDS), based on the principles of quantum mechanics, provide information-theoretic security, ensuring the integrity, authenticity, and non-repudiation of data transmission. With present QDS protocols, measurement-device-independent QDS (MDI-QDS) can resist all attacks on detections, yet it suffers from finite-size effect. In this work, we present and compare three parameter estimation models for finite-size analysis of two-decoy MDI-QDS. The first model is a commonly used model in previous schemes, and we propose two new models to improve the performance. Subsequently, we perform numerical simulations to evaluate the performance of the three models. The results demonstrate that the proposed methods are less affected by finite-size effect, thereby effectively enhancing the signature rate. This work contributes to the practical development of QDS. Copyright © 2025, The Authors. All rights reserved.

关键词： Authentication

来源：评论

学校读者我要写书评

暂无评论

Hybrid Implementation for Untrusted-node-based Quantum key Distribution network

arXiv

引用

arXiv 2025年

作者： Liu, Jingyang Zhou, Xingyu Ding, Huajian Xu, Jiaxin Zhang, Chunhui Li, Jian Wang, Qin Institute of quantum information and technology Nanjing University of Posts and Telecommunications Nanjing210003 China "Broadband Wireless Communication and Sensor Network Technology"Key Lab of Ministry of Education Ministry of Education Nanjing210003 China "Telecommunication and Networks"National Engineering Research Center NUPT Nanjing210003 China

Quantum key distribution (QKD) serves as a cornerstone of secure quantum communication, providing unconditional security grounded in quantum mechanics. While trusted-node networks have facilitated early QKD deployment, their vulnerability to node compromise underscores the need for untrusted-node architectures. Measurement-device-independent QKD (MDI-QKD) and twin-field QKD (TF-QKD) have emerged as leading candidates, addressing security vulnerabilities and extending transmission distances. Despite the wide adoptions in various fiber scaling, no integrated implementation of these two protocols has been demonstrated to date. Here, we present a hybrid system that seamlessly integrates TF-QKD and MDI-QKD into one untrusted-node-based architecture. Utilizing an efficient phase estimation method based on asymmetric interferometers, we convert twin-field global phase tracking to relative phase calibration, allowing near continuous running of both protocols. Experiments demonstrate secure finite-size key rates for sending-or-not-sending QKD and MDI-QKD over fiber distances of 150 to 431 km. The results align with theoretical simulations and show the ability to surpass the absolute repeaterless key capacity. Our work offers an unified framework for deploying multi-protocol QKD networks, laying the foundation for adaptable and scalable quantum infrastructures that can meet a wide range of security and performance needs. Copyright © 2025, The Authors. All rights reserved.

关键词： Quantum communication

来源：评论

学校读者我要写书评

暂无评论

Simplification of I-Vector Extraction for Speaker Identification

引用

Chinese Journal of Electronics 2016年第6期25卷 1121-1126页

作者： XU Longting YANG Zhen SUN Linhui Broadband Wireless Communication and Sensor Network Technology Key Lab Nanjing University of Posts and Telecommunications

The identity vector(i-vector) approach has been the state-of-the-art for text-independent speaker recognition, both identification and verification in recent years. An i-vector is a low-dimensional vector in the socalled total variability space represented with a thin and tall rectangular matrix. This paper introduces a novel algorithm to improve the computational and memory requirements for the application. In our method, the series of symmetric matrices can be represented by diagonal expression,sharing the same dictionary, which to some extent is analogous to eigen decomposition, and we name this algorithm Eigen decomposition like factorization(EDLF). Similar algorithms are listed for comparison, in the same condition,our method shows no disadvantages in identification accuracy.

关键词： Speaker identification Closed-set I-vector Symmetric matrix factorization

来源：评论

学校读者我要写书评

暂无评论

Cross-layer resource allocation based on equivalent bandwidth in OFDMA systems

引用

Journal of Systems Engineering and Electronics 2016年第4期27卷 754-762页

作者： Su Pan Cheng Li Sheng Zhang Danwei Chen Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts & Telecommunications

A quality of service（QoS） guaranteed cross-layer resource allocation algorithm with physical layer, medium access control（MAC） layer and call admission control（CAC） considered simultaneously is proposed for the full IP orthogonal frequency division multiple access（OFDMA） communication system, which can ensure the quality of multimedia services in full IP *** algorithm converts the physical layer resources such as subcarriers, transmission power, and the QoS metrics into equivalent bandwidth which can be distributed by the base station in all three layers. By this means, the QoS requirements in terms of bit error rate（BER）, transmission delay and dropping probability can be guaranteed by the cross-layer optimal equivalent bandwidth allocation. The numerical results show that the proposed algorithm has higher spectrum efficiency compared to the existing systems.

关键词： resource allocation equivalent bandwidth crosslayer optimization orthogonal frequency division multiple access(OFDMA)

来源：评论

学校读者我要写书评

暂无评论

Speech Signal Processing on Graphs: Graph Topology, Graph Frequency Analysis and Denoising

引用

Chinese Journal of Electronics 2020年第5期29卷 926-936页

作者： WANG Tingting GUO Haiyan LYU Bin YANG Zhen Broadband Wireless Communication and Sensor Network Technology Key Lab Nanjing University of Posts and Telecommunications

The paper investigates the hidden relationships among speech samples by applying graph tools. Specifically, we first estimate an applicable graph topology for unstructured speech signals, which can map speech signals into the vertex domain successfully and construct as Speech graph signals(SGSs). On the basis, we define a new graph Fourier transform for SGSs, which can investigate its related graph Fourier analysis. Moreover,we propose a new Graph structure spectral subtraction(GSSS) method for speech enhancement under different noisy environments. Simulation results show that the performance of the GSSS method can be significantly improved than the classical Basic spectral subtraction(BSS) method in terms of the average Segmental signal-tonoise ratio(SSNR), Perceptual evaluation of speech quality(PESQ) and the computational complexity.

关键词： Graph Fourier transform Graph topology graph frequency analysis speech processing graph topology unstructured speech signals GSSS method Speech graph Fourier analysis graph theory Fourier transforms speech quality classical Basic spectral subtraction method Denoising speech signal processing perceptual evaluation of speech quality computational complexity speech samples Graph structure spectral subtraction method Graph signal processing segmental signal-to-noise ratio speech enhancement graph tools Fourier analysis SGSs

来源：评论

学校读者我要写书评

暂无评论

On Least Squares Weighted Recursive Estimation of Clock Skew and Offset in wireless sensor networks

引用

Chinese Journal of Electronics 2017年第5期26卷 1041-1047页

作者： HU Bing SUN Zhixin Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Ministry of EducationNanjing University of Posts and Telecommunications

Three clock synchronization algorithms for wireless sensor networks(WSNs) in Pairwise broadcast synchronization(PBS) mechanism are *** include the joint Least squares estimator(LS),joint Least squares weighted estimator(LSW) and joint Least squares weighted Recursive estimator(R-LSW).For these estimators,the corresponding algorithms are derived and described by assuming a Gaussian random delay *** PBS,these estimators can achieve the Cramer-Rao lower bound(CRLB) for both listening node and active node without knowledge of the deterministic *** purpose of considering R-LSW is to reduce the use of storage space with the method of estimating while *** and analytical results verify that the estimators are efficient.

关键词： Clock synchronization wireless sensor networks(WSNs) Pairwise broadcast synchronization(PBS) Least squares estimator(LS)

来源：评论

学校读者我要写书评

暂无评论

LANDMARC Localization Algorithm Based on Weight Optimization

引用

Chinese Journal of Electronics 2018年第6期27卷 1291-1296页

作者： HU Bing PENG Huijun SUN Zhixin Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Ministry of EducationNanjing University of Posts and Telecommunications

In order to solve the problem that the difference of Received signal strength(RSS) between tags will become large when tags are close to the reader, which exists in LANDMARC system, a LANDMARC localization algorithm based on weight optimization is proposed in the paper. We optimize the weight by redefining the formulas of in-weight and ex-weight. In-weight formula is discussed under the free space propagation model. The definition of ex-weight is obtained by analyzing the relationship between RSS and distance under the log-distance path loss model. We evaluate the performance of the proposed algorithm and compare it with the algorithm based on normalized weight. The simulation results show the superior performance of the proposed algorithm in terms of location accuracy.

关键词： Location identification based on dynamic active RFID calibration(LANDMARC) system Radio frequency identification(RFID) Indoor localization Weight optimization

来源：评论

学校读者我要写书评

暂无评论

Outage performance analysis in cognitive wireless relay networks

引用

Research Journal of Applied Sciences, Engineering and technology 2012年第20期4卷 3958-3964页

作者： Yue, Wenjing Chen, Zhi Wang, Anyi Hu, Luoquan Wang, Lei Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunication Nanjng China

The analysis the outage performance of suggested Cognitive wireless Relay network (CWRN) which consists of a source, a destination and M cognitive relay nodes and M primary user nodes. In this study, we mainly study that the cognitive relay nodes impact on the outage performance of proposed CWRN over Rayleigh channels under both the peak and average interference power constraints. Firstly, considering a scenario with a single cognitive relay node, the optimal power control policies of the cognitive relay nodes are derived in order to achieve the minimum system outage probability under different interference power constraints. Then, to further improve outage performance, a scenario with multi-relay is also studied. Finally, the numerical simulations are presented. Numerical results show that substantial performance improves with the increase of the number of cognitive relay nodes and the power control policy under the average interference power constraint is more effective than that under the peak interference power constraint. © Maxwell Scientific Organization, 2012.

关键词： Cognitive radio

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：