检索结果-内蒙古大学图书馆

Ultra-compact and broadband polarization-insensitive mode-order converting power splitter

Chinese Optics Letters 2024年第3期22卷 36-41页

作者：陈浩琪姚润葵汪鹏君符强陈伟伟戴世勋孔德军林健金涛李军戴庭舸杨建义 Faculty of Electrical Engineering and Computer Science Ningbo UniversityNingbo 315211China College of Electrical and Electronic Engineering Wenzhou UniversityWenzhou 325035China College of Science and Technology Ningbo UniversityNingbo 315211China Laboratory of Infrared Materials and Devices The Research Institute of Advanced TechnologiesNingbo UniversityNingbo 315211China Department of Information Science and Electronics Engineering Zhejiang UniversityHangzhou 310027China

A polarization-insensitive mode-order converting power splitter using a pixelated region is presented and investigated in this *** TE_(0)and TM_(0)modes are injected into the input port,they are converted into TE_(1)and TM_(1)modes,which evenly come out from the two output *** finite-difference time-domain method and direct-binary-search optimization algorithm are utilized to optimize structural parameters of the pixelated region to attain small insertion loss,low crosstalk,wide bandwidth,excellent power uniformity,polarization-insensitive property,and compact *** results reveal that the insertion loss,crosstalk,and power uniformity of the fabricated device at 1550 nm are 0.57,-19.67,and 0.094 d B in the case of TE polarization,while in the TM polarization,the relevant insertion loss,crosstalk,and power uniformity are 0.57,-19.40,and 0.11 d *** a wavelength range from 1520 to 1600 nm,for the fabricated device working at TE polarization,the insertion loss,crosstalk,and power uniformity are lower than 1.39,-17.64,and 0.14 *** the case of TM polarization,we achieved an insertion loss,crosstalk,and power uniformity less than 1.23,-17.62,and 0.14 dB.

关键词： integrated optics optical waveguide polarization-insensitive property mode-order converting power splitter

来源：评论

学校读者我要写书评

暂无评论

Sparse Orthogonal Matching Pursuit-based Parameter Estimation for Integrated Sensing and Communications

arXiv

引用

arXiv 2025年

作者： Duong, Ngoc-Son Ngo, Khac-Hoang Dinh, Thai-Mai Nguyen, Van-Linh Faculty of Electronics and Telecommunications VNU University of Engineering and Technology Hanoi Viet Nam Linköping University Linköping Sweden Department of Computer Science and Information Engineering National Chung Cheng University Taiwan

Accurate parameter estimation such as angle of arrival (AOA) is essential to enhance the performance of integrated sensing and communication (ISAC) in mmWave multiple-input multiple-output (MIMO) systems. This work presents a sensing-aided communication channel estimation mechanism, where the sensing channel shares the same AOA with the uplink communication channel. First, we propose a novel orthogonal matching pursuit (OMP)-based method for coarsely estimating the AOA in a sensing channel, offering improved accuracy compared to conventional methods that rely on rotational invariance techniques. Next, we refine the coarse estimates obtained in the first step by modifying the Space-Alternating Generalized Expectation-Maximization algorithm for fine parameter estimation. Through simulations and mathematical analysis, we demonstrate that scenarios with shared AOA achieve a better Cramér-Rao lower bound (CRLB) than those without sharing. This finding highlights the potential of leveraging joint sensing and communication channels to enhance parameter estimation accuracy, particularly in channel or location estimation applications. © 2025, CC BY-NC-SA.

关键词： Cramer-Rao bounds

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Techniques for Advanced Large-Scale Data Processing

Deep Learning Techniques for Advanced Large-Scale Data Proce...

引用

International Conference on Computing and Networking technology (ICCNT)

作者： Mp Sunil Jyoti Shekhawat T. Vanaja Vazeer Ali Mohammed Shailesh J. Thaware Vaishali Singh Department of Electronics and Communication Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bangalore Karnataka India Department of Computer Science & Application Vivekananda Global University Jaipur India Department of Information Technology Prince Shri Venkateshwara Padmavathy Engineering College Chennai Department of Computer & Information System Lewis University Illinois USA Department of Computer Engineering Vishwakarma Institute of Technology Pune INDIA Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Deep getting to know techniques have become increasingly more popular due to their potential to improve huge-scale records processing performance. Leveraging specialized hardware which includes GPUs, deep getting to know algorithms can attain mind-blowing pace will increase compared to traditional algorithms. further, deep gaining knowledge of fashions can discover complicated non-linear relationships in big datasets, permitting greater accurate overall performance and less fake predictions. Latest advances in deep mastering have enabled it to be implemented to remedy a plethora of information processing duties, from photo recognition to natural language processing. CNNs, RNNs, and GANs are a number of the maximum famous deep gaining knowledge of fashions used in tackling complex data processing obligations. agencies consisting of Google, fb, and Amazon use these sophisticated frameworks to build predictive models that help improve numerous programs. Deep getting to know strategies offer exquisite ability to take massive-scale information processing to the following stage. corporations are increasingly more becoming privy to the emerging opportunities, and actively investing in deep mastering to liberate the untapped strength of their information.

关键词： Deep learning Accuracy Scalability Information processing Predictive models Data processing Prediction algorithms Hardware Natural language processing Optimization

来源：评论

学校读者我要写书评

暂无评论

Fast-OMRA: Fast Online Motion Resolution Adaptation for Neural B-Frame Coding

arXiv

引用

arXiv 2024年

作者： NguyenQuang, Sang Gao, Zong-Lin Ho, Kuan-Wei HoangVan, Xiem Peng, Wen-Hsiao Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan Faculty of Electronics and Telecommunications VNU University of Engineering and Technology Hanoi Viet Nam

Most learned B-frame codecs with hierarchical temporal prediction suffer from the domain shift issue caused by the discrepancy in the Group-of-Pictures (GOP) size used for training and test. As such, the motion estimation network may fail to predict large motion properly. One effective strategy to mitigate this domain shift issue is to downsample video frames for motion estimation. However, finding the optimal downsampling factor involves a time-consuming rate-distortion optimization process. This work introduces lightweight classifiers to determine the downsampling factor. To strike a good rate-distortion-complexity trade-off, our classifiers observe simple state signals, including only the coding and reference frames, to predict the best downsampling factor. We present two variants that adopt binary and multi-class classifiers, respectively. The binary classifier adopts the Focal Loss for training, classifying between motion estimation at high and low resolutions. Our multi-class classifier is trained with novel soft labels incorporating the knowledge of the rate-distortion costs of different downsampling factors. Both variants operate as add-on modules without the need to re-train the B-frame codec. Experimental results confirm that they achieve comparable coding performance to the brute-force search methods while greatly reducing computational complexity. © 2024, CC BY-NC-SA.

关键词： Signal distortion

来源：评论

学校读者我要写书评

暂无评论

Machine Learning based Beamwidth Adaptation for mmWave Vehicular Communications 16

Machine Learning based Beamwidth Adaptation for mmWave Vehic...

引用

16th IEEE Malaysia International Conference on Communication, MICC 2023

作者： Manic, Setinder Foh, Chuan Heng Kose, Abdulkadir Lee, Haeyoung Leow, Chee Yen Chatzimisios, Periklis Moessner, Klaus Suthaputchakun, Chakkaphong University of Surrey 5GIC & 6GIC Guildford United Kingdom Abdullah Gul University Department of Computer Engineering Kayseri Turkey School of Physics Engineering and Computer Science University of Hertfordshire Hatfield United Kingdom Universiti Teknologi Malaysia Wireless Communication Centre Johor Malaysia International Hellenic University Department of Information and Electronic Systems Engineering Thessaloniki Greece Technical University Faculty of Electronics and Information Technology Chemnitz Germany Bangkok University Electrical and Computer Engineering Department Khlong Nueng Thailand

ISBN: (纸本)9798350304343

The incorporation of mmWave technology in vehicular networks has unlocked a realm of possibilities, propelling the advancement of autonomous vehicles, enhancing interconnectedness, and facilitating communication for intelligent transportation systems (ITS). Despite these strides in connectivity, challenges such as high path-loss have arisen, impacting existing beam management procedures. This work aims to address this issue by improving beam management techniques, specifically focusing on enhancing the service time between vehicles and base stations through adaptive mmWave beamwidth adjustments, accomplished using a Contextual Multi-Armed Bandit Algorithm. By leveraging various conditions to train the ML agent of the Contextual Multi-Armed Bandit Algorithm, it seeks to learn about vehicle mobility profiles and optimize the usage of different antenna beamwidth settings to maximize seamless connection time. The extensive simulation results showcase the effectiveness of an adaptive beamwidth for mobility profiles, extending the connection time a vehicle experiences with a base station when compared to the existing strategies. © 2023 IEEE.

关键词： Base stations

来源：评论

学校读者我要写书评

暂无评论

Graphene Nanoribbon Based McCulloch-Pitts Neural Network

Graphene Nanoribbon Based McCulloch-Pitts Neural Network

引用

IEEE Conference on Nanotechnology

作者： F.-S. Dumitru M. Enachescu A. M. Antonescu N. Cucu-Laurenciu S. D Cotofana Faculty of Electronics Telecommunications and Information Technology National University of Science and Technology Politehnica Bucharest Romania High Energy Physics Department IMAPP Radboud University The Netherlands Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft AA The Netherlans

ISBN: (数字)9798350386240

ISBN: (纸本)9798350386257

In the context of an artificial intelligence and machine learning landscape that is evolving at an unprecedented pace, we propose a low power, high-speed, mixed-signal graphene nanoribbon-based (GNR) McCulloch-Pitts neuron (MCPN) implementation featuring programmable synaptic weights and inhibitory inputs. By definition, a generic MCPN is comprised of two parts, a weighted summation element and a decision element, called a soma. Our summation element implementation uses three distinct non-rectangular GNR devices, biased under specific conditions, to fulfill the roles of current source, low-side and high-side switches. The programmable excitatory and inhibitory synapses were obtained leveraging GNR SRAM cells and logic gates, hence providing the flexibility needed by real-world applications. The decision element's threshold activation function was implemented using a chain of GNR inverter structures which manifest the function's characteristic in the analog domain. Modulation of the decision element's threshold is achieved indirectly by means of a configurable resistive load which is varied depending on the configuration stored in SRAM. Our benchmark results, obtained using a generic 5 by 5 pixel pattern recognition application, reveal that the GNR-based implementation achieves 3.5× less power consumption, 20 × higher speed, while occupying 3 × less active area when compared to its FinFET analog circuit counterpart.

关键词： Power demand Graphene Neurons Symbols Logic gates FinFETs SRAM cells

来源：评论

学校读者我要写书评

暂无评论

Performance Improvement of Grid-Tied Cascaded H-Bridge Inverter Using Advanced Single-Carrier PWM Scheme

Performance Improvement of Grid-Tied Cascaded H-Bridge Inver...

引用

Australasian Universities Power engineering Conference, AUPEC

作者： Sudipto Mondal Md. Kamal Hosain Shuvra Prokash Biswas Joysree Nath Md. Rabiul Islam Parvez Mahmud Narottam Das Department of Electronics & Telecommunication Engineering Rajshahi University of Engineering & Technology Rajshahi Bangladesh School of Electrical Computer &Telecommunications Engineering University of Wollongong NSW Australia Faculty of Science University of Technology Sydney Ultimo NSW Australia School of Engineering and Technology Central Queensland University Melbourne VIC Australia

ISBN: (数字)9798350377941

ISBN: (纸本)9798350377958

Grid-tied solar photovoltaic (PV) systems are becoming increasingly prevalent as a result of recent advancements and the popularity of solar photovoltaic panels. The control strategy used has a significant impact on these systems’ dependability and performance. In order to link PV systems to medium-voltage grids, this paper presents a seventh harmonic injected single carrier pulse width modulation (SHISCPWM) technique for a cascaded H-bridge (CHB) inverter. In contrast to the stablished phase disposition PWM (PDPWM) method, the suggested SHISCPWM generates gate pulses in the CHB by utilizing only a single carrier and a seventh harmonic saturated signal. On digital signal processor (DSP)/ field programmable gate array (FPGA) platforms, this innovative SHISCPWM technique eases implementation and lessens computational load. However, the goal of the proposed SHISCPWM is to guarantee the thermal stability of junction temperature of the power semiconductor devices. Again, the SHISCPWM seeks to minimize the total harmonic distortion (THD) of CHB inverter, which will result in lower semiconductor power losses and higher efficiency. In addition to optimizing DC bus consumption, the proposed SHISCPWM reduces switching and conduction losses.

关键词： Photovoltaic systems Stability criteria Pulse width modulation Power system stability Logic gates Harmonic analysis Inverters Junctions Thermal stability Power harmonic filters

来源：评论

学校读者我要写书评

暂无评论

Channel Estimation using LS and MMSE Channel Estimation Techniques for MIMO-OFDM Systems 4

Channel Estimation using LS and MMSE Channel Estimation Tech...

引用

4th International Congress on Human-computer Interaction, Optimization and Robotic Applications, HORA 2022

作者： Ahmed, Ali Saadoon Hamdi, Mustafa Maad Abood, Mohammed Salah Khaleel, Arshad Mohammed Fathy, Maha Khaleefah, Shihab Hamad Al-Maarif University College Department of Computer Science Al-Anbar Iraq Al-Maarif University College Department of Computer Engineering Techniques Al-Anbar Iraq Beijing Institute of Technology School of Information and Electronics Engineering Beijing China Altinbas Universiti Department of Electrical and Computer Engineering Istanbul Turkey Al-Maarif University College Faculty of Computer Science Anbar31001 Iraq

ISBN: (纸本)9781665468350

The conventional strategies utilized for channel assessment don't exploit the multipath lack. In MIMO-OFDM frameworks, channel assessment is critical for computing framework execution. There are pre-codes and books higher than obscure channel boundaries using channel status data (CSI). Multiple Input Multiple Output (MIMO) systems are practical innovations that can be used to meet the growing demand for remote communication and fast data transfers. To predict the transmission and gathering of data between radio wires, various procedures for channel assessment can be used. The article focuses on a channel estimation technique that employs LS and MMSE algorithms and is based on pilot-assisted block type training symbols. The results for the BER and SNR scenarios were presented using the LS (least squares) and MMSE assessment techniques. The bit blunder rate (BER) is tested for various computerized tweak plans with various sign to-commotion (SNR) values in the OFDM framework. This resulted in fantastic results. Because of this, it can be concluded that the least-squares assessment strategy is a valuable method for assessing channels. © 2022 IEEE.

关键词： Orthogonal frequency division multiplexing

来源：评论

学校读者我要写书评

暂无评论

A Framework for Democratizing Open-Source Decision-Making using Decentralized Autonomous Organization

A Framework for Democratizing Open-Source Decision-Making us...

引用

Computing and Informatics (ICCI), International Conference on

作者： Khalifa H. Afifi Khaled M. Fouad Heba K. Aslan Faculty of Information Technology and Computer Science Nile University Cairo Egypt Faculty of Computers and Artificial Intelligence Benha University Faculty of Computers and Engineering New Mansoura University Egypt Informatics Department Electronics Research Institute (ERI) Cairo Egypt Center of Informatics Science Faculty of Information Technology and Computer Science Nile University Cairro Egypt

The open Source Software (OSS) became the backbone of the most heavily used technologies, including operating systems, cloud computing, AI, Blockchain, Bigdata Systems, IoT, and many more. Although the OSS individual contributors are the primary power for developing the OSS projects, they do not contribute to the OSS project's decisionmaking as much as their contributions in the OSS Projects development. This paper proposes a framework to democratize the OSS Project's decision-making using a blockchain-related technology called Decentralized Autonomous Organization (DAO). Using DAO, contributors get incentive tokens as a reward in return for contributions. The earned tokens can be used in the process of decision-making governance. This governance model tends to allow OSS individual contributors to have a public voice in the OSS project's development roadmap in particular, and the OSS decision making governance in general.

关键词：

来源：评论

学校读者我要写书评

暂无评论

IoT-Enabled Deep Learning Framework for Smart Infant Health Monitoring

IoT-Enabled Deep Learning Framework for Smart Infant Health ...

引用

International Conference on ent Computing and Control Systems (ICICCS)

作者： Madhu R U.V. Anbazhagu R. Santhana Krishnan Kruthika Paulraj Ezhil E. Nithila R. Umesh Department of Computer Science and Engineering Ramco Institute of Technology Rajapalayam India Department of Computing Technologies School of Computing College of Engineering and Technology Faculty of Engineering and Technology SRM Institute of Science and Technology Chennai India Department of Electronics and Communication Engineering SCAD College of Engineering and Technology Cheranmhadevi India Department of Information Technology Sona College of Technology Salem India Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai India Department of Information Technology Velammal College of Engineering and Technology Madurai India

ISBN: (数字)9798331512088

ISBN: (纸本)9798331512095

The Intelligent Baby Monitoring System integrates AI-driven cry detection, sleep tracking, and environmental safety analysis to enhance infant care. The system employs CNN-BiLSTM and Wav2Vec2.0 for cry classification, distinguishing between hunger, pain, and sleepy cries based on pitch, energy, and duration. Sleep monitoring utilizes YOLOv8, OpenPose, and LSTM to analyze sleep stages, detecting awake, asleep, restless, and distress states through body movement intensity. Anomaly detection is performed using an LSTM Autoencoder, identifying abnormal gas levels (MQ-135), temperature and humidity fluctuations (DHT22), and deviations in heart rate and SpO 2 levels (MAX30102). Heart rate monitoring leverages 1D-CNN and LSTM, classifying conditions such as bradycardia (<100 bpm) and tachycardia (>180 bpm), while oxygen saturation levels below 90% indicate hypoxia. Cradle safety monitoring employs YOLOv8 and CNN-LSTM, detecting movement patterns such as excessive shaking and escape attempts, with acceleration thresholds exceeding 0.7g triggering alerts. The system is implemented on an NVIDIA Jetson Nano, ensuring real-time inference with optimized TensorRT models. Data transmission to AWS IoT Core enables cloud-based storage and remote monitoring through a mobile application. By integrating deep learning, edge AI, and cloud computing, this system offers an efficient, intelligent, and real-time solution for infant monitoring, ensuring timely alerts and enhanced caregiver response. The proposed system is evaluated across multiple performance metrics, demonstrating high accuracy in cry classification, sleep tracking, and anomaly detection, making it a robust tool for infant safety and well-being.

关键词： Deep learning Pediatrics Cloud computing Accuracy Edge AI Real-time systems Safety Monitoring Anomaly detection Long short term memory

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：