检索结果-内蒙古大学图书馆

Application of New Companding Techniques on the DWT-Based SC-FDMA System

Annals of Data Science 2022年第6期9卷 1149-1159页

作者： Abd El-Rahman, Amal Fawzy Abd Elnaby, Mustafa M. Khamis, Salah Napoleon, Sameh Abd El-Samie, Fathi E. Electronics and Communications Department Faculty of Engineering Tanta University Tanta Egypt Department of Electronics and Electrical CommunicationsEngineering Faculty of Electronic Engineering MenoufiaUniversity Menouf32952 Egypt Department of Information Technology Collegeof Computer and Information Sciences Princess Nourah BintAbdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia Department of Electronics and Electrical Communication Engineering Higher Institute for Engineering and Technology KafrElsheikh Egypt

Orthogonal Frequency Division Multiplexing (OFDM) is the most popular multicarrier communication technique, but its disadvantage is the large Peak-to-Average Power Ratio (PAPR). In recent years, different researchers presented several techniques to avoid this problem such as companding techniques. Moreover, the Single-Carrier Frequency Division Multiple Access (SC-FDMA) system is a popular system in mobile communications because of its advantage of low PAPR, but reducing its PAPR is still an open research issue. So, an extension of the work applied on OFDM to SC-FDMA is adopted in this paper to reduce the PAPR, while achieving a low Bit Error Rate (BER). New companding schemes are adopted in this paper with the help of the Discrete Wavelet Transform (DWT) in the presence of channel degradations for lowering the PAPR of the SC-FDMA system, while achieving a low BER. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Frequency division multiple access

来源：评论

学校读者我要写书评

暂无评论

A Method for Vietnamese Sign Language Recognition Using a Fusion of RGB and Depth Information Based on an Inflated 3D ConvNet 3rd

A Method for Vietnamese Sign Language Recognition Using a Fu...

引用

3rd International Conference on Advances in Information and Communication Technology, ICTA 2024

作者： Nguyen, Xuan-Phuoc Nguyen, Thi-Oanh Nguyen, Van-Toi Faculty of Computer Science PHENIKAA Univesity Yen Nghia Ha Dong Hanoi12116 Viet Nam ICT Department FPT University Hanoi Viet Nam Faculty of Electrical and Electronic Engineering PHENIKAA University Yen Nghia Ha Dong Hanoi12116 Viet Nam

ISBN: (纸本)9783031809422

We propose a method for Vietnamese Sign Language (VSL) recognition using a fusion of RGB and Depth information based on the Inflated 3D ConvNet (I3D) architecture. Our approach applies I3D feature extraction independently to RGB and Depth data, concatenates the extracted features, and processes them through the final classification layer. This method leverages the complementary strengths of both data types, enhancing recognition performance. Experimental results show that our method outperforms the original I3D and other fusion strategies, including Early Fusion and Late Fusion. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Fusion of RGB and Depth Inflated 3DConvNet Sign Language Recognition

来源：评论

学校读者我要写书评

暂无评论

Centralized RSU Deployment Strategy for Effective Communication in Multi-hop Vehicular Adhoc Networks (VANETs) 6th

Centralized RSU Deployment Strategy for Effective Communicat...

引用

6th International Conference on Innovative Computing and Communication, ICICC 2023

作者： Rashid, Sami Abduljabbar Audah, Lukman Hamdi, Mustafa Maad Abdulsattar, Nejood Faisal Mutar, Mohammed Hasan Alkhafaji, Mohamed Ayad Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia Batu Pahat Johor Parit Raja86400 Malaysia Department of Computer Engineering Technology Al-Maarif University College Al-Anbar Iraq Department of Computer Technical Engineering College of Information Technology Imam Ja’afar Al-Sadiq University Al-Muthanna Baghdad66002 Iraq National University of Science and Technology DhiQar Iraq

ISBN: (纸本)9789819940707

Due to the advent of smart cities, vehicular technologies are high focus to perform intelligent transmission. Road traffic control and accident control becomes a primary tasks in Vehicular Adhoc Networks (VANETs). In VANETs communication is ineffective without presence of Road Side Units (RSUs). In some places due to lack of RSUs data transmission is improve as well as end to end delay and routing overhead is increased during the time of communication so effective RSU deployment is very essential to provide effective communication in multi-hop VANETs. In this paper, Centralized RSU Deployment Strategy is proposed to control and monitor the traffic density of the vehicle. The parameters which are considered for the process of centralized RSU deployment strategy are centralization scale, past transmission rate and location identification. To analysis the performance of the network the simulation is carried out in NS2.35 and SUMO. The parameters which are taken for the performance analysis are packet delivery ratio, end to end delay, routing overhead and packet loss. In order to execute comparative analysis the recent research works are considered which are AVRCV and RDSTDV. From the outcome it is understood that the proposed CRDSMV approach achieves 70–200 ms lower end to end delay, 7–14% improved packet delivery ratio, and 50–300 packets lower routing overhead and 50–240 Kbps improved throughputs when compared with the earlier methods AVRCV and RDSTDV. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Roads and streets

来源：评论

学校读者我要写书评

暂无评论

Two-step registration of rigid and non-rigid MR-iUS for brain shift compensation using transfer learning

Two-step registration of rigid and non-rigid MR-iUS for brai...

引用

International Symposium on Artificial Intelligence and Signal Processing (AISP)

作者： Amir Hossein Jalalzadeh Seyed Saeid Talebi Mehrdad Hashemi Kamangar Department of Biomedical Engineering Engineering faculty Shahed University Tehran Iran Department of Electrical and Computer Engineering Noshirvani University Babol Iran Department of Electrical and Electronic Engineering Engineering Faculty Shomal University Amol Iran

Accurate removal of brain tumors is always one of the most important challenges for surgeons, as the continuous change of the brain state after opening the skull and releasing the resulting pressure causes the tumor state to change. By registration of preoperative MR images on intraoperative ultrasound images, the extent of this change is estimated and a new image of the brain is created. The result shows the changes and shifts in the brain, and the surgeon removes the tumor based on this image. Image registration using new deep learning methods has attracted the attention of many researchers due to its high efficiency and accuracy. In this paper, the images of 22 male and female patients with grade 2 glioma tumors were used to evaluate the proposed method. MR images of the patients were taken before surgery, while ultrasound images were taken during surgery and after cranial incision. The deep network used in this paper to compensate for non-rigid changes is voxel morph. All images were fed to the pre-trained network in pairs, and the results are reported for each individual. The average error of all images for the proposed method is 3.56 ± 1.72. This shows the improvement in performance compared to the previous methods since in this work the landmarks were not used in training phase.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Cancelable Biometrics Based on Quaternion Adaptive Filter Optimization for Security Applications 6

Cancelable Biometrics Based on Quaternion Adaptive Filter Op...

引用

6th International Conference on Computing and Informatics, ICCI 2024

作者： Nasr, Mahmoud Piórkowski, Adam Mah, Pascal Muam Abd El-Samie, Fathi E. Department of Biocybemetics and Biomedical Engineering AGH University of Krakow Cracow Poland Faculty of Engineering and Technology Future University in Egypt Cairo Egypt Department of Technical Informatics and Telecommunications AGH University of Krakow Cracow Poland Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

ISBN: (纸本)9798350373875

This study introduces a unique cancelable face recognition technique that depends on adaptive filters and quaternion mathematics. The whale optimization is also applied to determine the optimal parameter settings for best performance. The primary concept of the suggested model revolves around the concealment of facial characteristics before their utilization in the face recognition process. The primary aim of this procedure is to guarantee the confidentiality of users' personal information throughout the enrollment and verification stages of the biometric system, particularly when the database is compromised and the stored biometric templates are altered. In this context, the color facial image is utilized to construct a quaternion. After that, a mask image is employed in a separate quaternion. The cancelable templates are obtained by using the input and mask images represented in quaternion format and applying an adaptive filter on both of them. This process involves preserving the weights of the adaptive filter. Investigation of the suggested tehnique performance demonstrates that the obtained templates lead to low (EER) and a large Area under the ROC curve. © 2024 IEEE.

关键词： Adaptive filters

来源：评论

学校读者我要写书评

暂无评论

Error performance of DDPSK receiver in the presence of composite fading

引用

IEEE Access 2025年 13卷 98066-98075页

作者： Djordjevic, Goran T. Petkovic, Milica Milosevic, Nenad Vasic, Bane University of Nis Faculty of Electronic Engineering 18000 Serbia University of Novi Sad Faculty of Technical Sciences Novi Sad 21000 Serbia The University of Arizona Department of Electrical and Computer Engineering Tucson 85721 AZ United States

We investigate the justification for implementing double differential phase-shift keying (DDPSK) instead of differential phase-shift keying (DPSK) in the presence of carrier frequency offset (CFO) over wireless channels affected by thermal noise, multipath fading, and shadowing. When shadowed multipath fading is modeled using the Fisher-Snedecor F distribution, we present the probability density function (PDF) of the received composite signal phase in the form of the Fourier series and derive novel analytical expressions for its Fourier coefficients. Furthermore, we present analytical expressions for the symbol error probability (SEP) in detection of DDPSK and DPSK signals over such shadowed fading channels. These expressions are derived in the form of infinite series followed by the appropriate proof of convergence. We determine the necessary number of terms to achieve a given accuracy. Derived expressions allow us to illustrate the superiority of DDPSK compared to DPSK in the presence of CFO. We analyze the applicability of DDPSK across various values of normalized CFO, multipath fading depth, and shadowing severity, considering different modulation orders. Our key conclusion is that DDPSK outperforms DPSK when CFO values are higher. Additionally, as the modulation order increases, CFO has a stronger impact on SEP degradation in DPSK detection. Notably, at higher CFO values, DDPSK superiority becomes evident even at lower signal-to-noise ratio levels. © 2013 IEEE.

关键词： double differential phase-shift keying Error probability Fourier series multipath fading shadowing

来源：评论

学校读者我要写书评

暂无评论

Phase chimera states on nonlocal hyperrings

引用

Physical Review E 2024年第2期109卷 L022201-L022201页

作者： Riccardo Muolo Thierry Njougouo Lucia Valentina Gambuzza Timoteo Carletti Mattia Frasca Department of Systems and Control Engineering Tokyo Institute of Technology Tokyo 152-8552 Japan Department of Mathematics University of Namur B5000 Namur Belgium naXys Namur Institute for Complex Systems University of Namur B5000 Namur Belgium Faculty of Computer Science University of Namur B5000 Namur Belgium Department of Electrical and Electronic Engineering University of Buea P.O. Box 63 Buea Cameroon Department of Electrical Electronics and Computer Science Engineering University of Catania 95125 Catania Italy Istituto di Analisi dei Sistemi ed Informatica “A. Ruberti” IASI-CNR 00185 Roma Italy

Chimera states are dynamical states where regions of synchronous trajectories coexist with incoherent ones. A significant amount of research has been devoted to studying chimera states in systems of identical oscillators, nonlocally coupled through pairwise interactions. Nevertheless, there is increasing evidence, also supported by available data, that complex systems are composed of multiple units experiencing many-body interactions that can be modeled by using higher-order structures beyond the paradigm of classic pairwise networks. In this work we investigate whether phase chimera states appear in this framework, by focusing on a topology solely involving many-body, nonlocal, and nonregular interactions, hereby named nonlocal d-hyperring, (d+1) being the order of the interactions. We present the theory by using the paradigmatic Stuart-Landau oscillators as node dynamics, and we show that phase chimera states emerge in a variety of structures and with different coupling functions. For comparison, we show that, when higher-order interactions are “flattened” to pairwise ones, the chimera behavior is weaker and more elusive.

关键词： Chimera states Collective behavior in networks Dynamics of networks Pattern formation Synchronization Synchronization transition

来源：评论

学校读者我要写书评

暂无评论

When Zero-Trust Meets Federated Learning

When Zero-Trust Meets Federated Learning

引用

2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Zhang, Xinran Wang, Dan Zhu, Yifei Chen, Weilong Chang, Zheng Han, Zhu The Hong Kong Polytechnic University Department of Computing Hong Kong Shanghai Jiao Tong University UM-SJTU Joint Institute Shanghai China University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu China University of Jyväskylä Faculty of Information Technology Jyväskylä Finland University of Houston Department of Electrical and Computer Engineering HoustonTX United States Kyung Hee University Department of Computer Science and Engineering Seoul Korea Republic of

ISBN: (纸本)9798350351255

Nowadays, Federated Learning (FL) has emerged as a promising and critical machine learning scheme to protect data privacy and reduce communication overhead. As the scale and connectivity expand in the FL system, enhancing the model's robustness against security threats from malicious clients grows ever more critical. An effective defensive solution involves selecting benign clients appropriately, thereby mitigating the vulnerability of the FL system to malicious attacks. However, clients exhibit varying behaviors over time, which complicates the task of accurately modeling their future trustworthiness. Moreover, blindly trusting clients with high trust values poses risks, given the potential for severe losses from betrayal. To tackle these problems, we propose a zero-trust policy in FL aimed at establishing continuous trust in each client while maintaining skepticism towards potential betrayal attacks. Specifically, we develop a Dirichlet-based trust evaluation technique to enable a comprehensive selection of trustworthy participants. This technique leverages the posterior distribution to estimate clients' trust values from their evolving behavior records over time. Then, we anticipate potential betrayal from a selected client and formulate a min-max optimization problem to minimize the worst-case betrayal loss, thereby boosting the system's betrayalaware robustness. Next, we convert this problem into a convex optimization problem and utilize the interior point method for resolution. We conduct extensive simulations to validate the efficacy of our proposed zero-trust policy in accurately assessing trust and enhancing the model's robustness to betrayal. © 2024 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Self-Supervise Reinforcement Learning Method for Vacant Parking Space Detection Based on Task Consistency and Corrupted Rewards

引用

IEEE Transactions on Intelligent Transportation Systems 2024年第2期25卷 1346-1363页

作者： Nguyen, Manh-Hung Chao, Tzu-Yin Hsiao, Ching-Chun Li, Yung-Hui Huang, Ching-Chun Hcm University of Technology and Education Faculty of Electrical Electronic Engineering Ho Chi Minh City700000 Viet Nam National Yang Ming Chiao Tung University Department of Computer Science Hsinchu300093 Taiwan Hon Hai Research Institute Ai Research Center New Taipei City114699 Taiwan

This paper proposes a novel task-consistency learning method that enables us to train a vacant space detection network (target task) based on the logic consistency with the semantic outcomes from a flow-based motion behavior classifier (source task) in a parking lot. Note that the source task can introduce false detection during task-consistency learning, which implies noisy rewards or supervision. The target network can be trained in a reinforcement learning setting by appropriately designing the reward mechanism upon semantic consistency. We also introduce a novel symmetric constraint to detect corrupted samples and reduce the effect of noisy rewards. Unlike conventional corrupted learning methods that use only training losses to identify corrupted samples, our symmetric constraint also explores the relationship among training samples to improve performance. Compared with conventional supervised detection methods, the main contribution of our work is the ability to learn a vacant space detector via semantic consistency rather than supervised labels. The dynamic learning property allows the proposed detector to be easily deployed and updated in various lots without heavy human loads. Experiments demonstrate that our noisy task consistency mechanism can be successfully applied to train a vacant space detector from scratch. © 2000-2011 IEEE.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Design and Application of Programmable Analog Computing Circuit for Kalman Filter Algorithm Based on Memristive Array

IEEE Transactions on Circuits and Systems for Artificial Int...

引用

IEEE Transactions on Circuits and Systems for Artificial Intelligence 2024年第2期1卷 272-284页

作者： Pingdan Xiao Sichun Du Zhengmiao Wei Qinghui Hong Shiping Wen College of Computer Science and Electronic Engineering Hunan University Changsha China Australian AI Institute Faculty of Engineering and Information Technology University of Technology Sydney Sydney NSW Australia

Kalman Filter algorithm is a crucial tool for estimating the state of dynamic systems in the presence of numerous uncertainties, which plays a pivotal role in various application scenarios such as information fusion and deep learning. However, current accelerators and hardware face limitations in terms of both latency and performance overhead when executing the Kalman Filter algorithm. Aiming at the above problem, we firstly propose a programmable circuits based on memristors for full process of Kalman Filter algorithm, which can efficiently run Kalman Filter algorithm with the advantage of analog circuits in parallel and fast computing, which achieve computing speed increasing in order of magnitude. Moreover, the empowerment of programmability from memristors avoid intensive memory access. For the problem how to linearly adjust weight for the memristor, we propose a new memristor-based programmable unit, the corresponding crossbar and method in order to achieve linear weight adjustment. The evaluation shows that the proposed circuits not only has over 95 $\%$ accuracy for 32-th order parameter matrix in Kalman Filter algorithm, but also has good robustness against some non-ideal factors it can still achieve 90 $\%$ accuracy under 10 $\%$ noise interference. The evaluating results of performance also show that it reduces energy consumption by 3.1 $\times$ and 8.9 $\times$ , compared with corresponding VLSI and FPGA accelerator, respectively. Moreover, an improved image fusion algorithm and circuit based on the proposed Kalman Filter circuits is proposed, which achieve good image fusion and speedup in computing time by 82.6 $\times$ and 121.3 $\times$ , compared with corresponding ASIC and FPGA, respectively.

关键词： Memristors Circuits Kalman filters Covariance matrices Artificial intelligence Analog circuits Noise Power demand Image fusion Field programmable gate arrays

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：