检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

2,922 篇 会议
20 篇 期刊文献
14 册 图书

馆藏范围

2,956 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,963 篇 工学
- 1,322 篇 计算机科学与技术...
- 947 篇 软件工程
- 818 篇 信息与通信工程
- 549 篇 电气工程
- 287 篇 控制科学与工程
- 262 篇 电子科学与技术（可...
- 190 篇 仪器科学与技术
- 172 篇 生物医学工程（可授...
- 160 篇 机械工程
- 160 篇 生物工程
- 110 篇 网络空间安全
- 96 篇 光学工程
- 91 篇 动力工程及工程热...
- 77 篇 材料科学与工程（可...
- 75 篇 化学工程与技术
- 70 篇 石油与天然气工程
- 58 篇 交通运输工程
- 51 篇 安全科学与工程
864 篇 理学
- 459 篇 数学
- 263 篇 物理学
- 184 篇 生物学
- 140 篇 化学
- 138 篇 统计学（可授理学、...
- 66 篇 系统科学
397 篇 管理学
- 236 篇 管理科学与工程(可...
- 196 篇 图书情报与档案管...
- 81 篇 工商管理
223 篇 医学
- 198 篇 临床医学
- 115 篇 基础医学(可授医学...
- 81 篇 药学(可授医学、理...
38 篇 法学
30 篇 经济学
23 篇 农学
18 篇 教育学
14 篇 军事学
3 篇 文学

主题

223 篇 signal processin...
117 篇 signal processin...
101 篇 data mining
76 篇 feature extracti...
68 篇 big data
68 篇 digital signal p...
57 篇 data acquisition
54 篇 signal to noise ...
50 篇 machine learning
48 篇 deep learning
46 篇 data models
40 篇 support vector m...
34 篇 training
32 篇 electroencephalo...
31 篇 data processing
31 篇 real-time system...
30 篇 array signal pro...
28 篇 image processing
28 篇 accuracy
26 篇 neural networks

机构

49 篇 maharishi school...
37 篇 centre of interd...
16 篇 department of ar...
15 篇 vishwakarma inst...
12 篇 department of el...
12 篇 department of co...
11 篇 department of sc...
11 篇 vivekananda glob...
9 篇 department of co...
8 篇 department of el...
8 篇 chitkara univers...
8 篇 prince shri venk...
8 篇 prince shri venk...
8 篇 key laboratory o...
8 篇 vivekananda glob...
8 篇 department of el...
7 篇 school of comput...
7 篇 key laboratory o...
7 篇 american interna...
7 篇 insight sfi rese...

作者

7 篇 md. rifat hazari
7 篇 hamdulla askar
7 篇 chakravarthi bha...
6 篇 kumaresan prasan...
6 篇 ablimit mijit
6 篇 ahmad tohari
6 篇 gao yanxia
6 篇 liu yiwen
5 篇 abir ahmed
5 篇 vikrant bhateja
5 篇 suresh chandra s...
5 篇 wang wei
5 篇 bekkay hajji
5 篇 chang chin-chen
5 篇 ramakrishnan ram...
5 篇 md. saniat rahma...
5 篇 zhang ying
4 篇 li li
4 篇 priyadharshini r...
4 篇 liu xin

语言

2,838 篇 英文
111 篇 其他
15 篇 中文
1 篇 俄文

检索条件"任意字段=3rd International Conference on Signal and Data Processing, ICSDP 2023"

共 2956 条记录，以下是651-660 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Simulation analysis and modeling of local discharge sensor 3

Simulation analysis and modeling of local discharge sensor

引用

3rd international conference on Intelligent Power and Systems, ICIPS 2023

作者： Xing, Yulong Han, Xueyu Yu, Qian'ao Wang, Yonggui Hu, Yuanyuan Mei, Xinsu State Grid Information & Telecommunication Group CO. LTD Beijing China State Grid Beijing Electric Power CO. Beijing China

ISBN: (纸本)9798350328691

Local discharge detection is an important technology used to evaluate the state of electrical equipment. It can realize early fault diagnosis, accident prevention, life extension and operation efficiency improvement of electrical equipment, provide scientific basis for equipment management and maintenance, and ensure the safe and stable operation of power system. The office release detection is realized by using the office release sensor, which is the core component of the office release detection, and plays the role of collecting, transmitting and transforming the office release signal, providing the necessary data basis for the office release detection. In this paper, the common detection technology and the local discharge sensor are introduced, and the failure mechanism of the local discharge sensor is studied by establishing the failure physical model of the local discharge sensor and simulating the stress environment. The 3D model of F-P sensor in transformer oil was established by ANSYS finite element simulation software and verified by simulation. The influence of liquid insulating dielectric on the characteristic parameters of partial discharge detection was analyzed. ©2023 IEEE.

关键词： 3D modeling

来源：评论

学校读者我要写书评

暂无评论

Third international conference on Digital signal and Computer Communications, DSCC 2023

Third International Conference on Digital Signal and Compute...

引用

3rd international conference on Digital signal and Computer Communications, DSCC 2023

ISBN: (纸本)9781510666559

The proceedings contain 73 papers. The topics discussed include: road traffic status discrimination method based on data fusion of multiple floating vehicles;traffic sign reflectivity detection method based on driver's visual recognition;a belief propagation cooperative localization algorithm in GNSS-loss environments;an integrated algorithm of transparency retrieval;research on 5G differential protection data compression transmission technology;optimization of radiation shielding scheme for Jupiter spacecraft based on genetic algorithm;bidirectional consistency of multi-agent based on data-driven;research on mung bean variety identification algorithm based on machine learning and hyperspectral technology;research and analysis of blockchain system based on computer big data model;and deep clustering model for time-series data based on recurrence plot and variational auto-encoder.

关键词：

来源：评论

学校读者我要写书评

暂无评论

The research on data acquisition and processing method of photovoltaic special metering protection unit based on LMS adaptive filtering 3

The research on data acquisition and processing method of ph...

引用

2022 3rd international conference on Smart Grid and Energy Engineering, SGEE 2022

作者： Fu, Zhaohui Chen, Zhiru Kong, Hongwei Jiang, Guixiang System Integration Department Henan XJ Metering Co. Ltd. Henan Xuchang461000 China Metering Center State Grid Shandong Electric Power Company Marketing Service Center Shandong Jinan250000 China

In order to solve the problem of synchronous acquisition of multi-parameter data of photovoltaic special metering protection unit and reduce the noise pollution of sensor data, this paper designs a multi-parameter data acquisition system of photovoltaic special metering protection unit;The system uses RN7326 and SWM32F103R chips as the main and auxiliary microprocessors, and designs a scheme of multi-sensor signal filtering and interface resource acquisition;The standardized data communication protocol is studied and designed to realize the synchronous data acquisition of multiple sensors;Finally, the LMS (Least mean square) based on adaptive filtering method is used to reduce the noise of multi-parameter data. In this paper, the temperature sensor pt100 is taken as an example to conduct temperature acquisition and filtering processing experiments. After data filtering, the noise above 1Hz is basically eliminated, and the noise pollution is effectively reduced when the noise amplitude is less than 1Hz, and the accuracy of sensor data is improved. © Published under licence by IOP Publishing Ltd.

关键词： Adaptive filtering

来源：评论

学校读者我要写书评

暂无评论

Deep Reinforcement Learning (DRL) based data analytics framework for Edge based IoT devices latency and resource optimization 3

Deep Reinforcement Learning (DRL) based data analytics frame...

引用

3rd international conference on Advances in Computing, Communication, Embedded and Secure Systems, ACCESS 2023

作者： Majjari, Sudhakar Anne, Koteswara Rao George, Joseph Kalasalingam Academy of Research and Education Department of CSE Tamil Nadu Krishnankoil India Adi Shankara Institute of Engg. and Technology Department of CSE Kaladyi India

ISBN: (纸本)9798350346169

Internet of Things (IoT) trends show rising data processing computational needs. Sensor data is uploaded to backend cloud nodes before data analyses at the network edge. IoT devices are usually resource-constrained and unable to execute operations quickly and accurately. Cloud servers are impractical and increase communication overhead. Cloud platforms offer machine learning services with pretrained models to understand IoT data. To use the cloud service, personal data must be transferred, and network problems may impede timely analysis results. data and analysis are shifting to edge platforms to solve these concerns. Most edge devices can't analyze and train a lot of data. Edge-enabled systems provide efficient compute and control at the network edge to reduce scalability and latency. IoT applications provide large heterogeneous data, which makes edge computing difficult. To solve this issue, Deep Reinforcement Learning (DRL) based data analytics framework for Edge based IoT devices to enable devices to execute tasks jointly, leveraging proximity and resource complementarity. It supports parallel data input and strengthen the comprehensive communication overhead handling through data scheduling optimization. The simulation results conveys that the proposed approach uses DRL to optimize execution accuracy and time without requiring a priori IoT node information. Moreover, the average delay time, percentage of failure and cost of rewards are computed in which being compared with the existing scheduling methods includes Proximal Policy Optimization technique (PPO), and Deep Deterministic Policy Gradient technique (DDPG). © 2023 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Algorithms for Secure and Efficient Compression of Genomic Sequence data 3

Deep Learning Algorithms for Secure and Efficient Compressio...

引用

3rd IEEE international conference on Technology, Engineering, Management for Societal Impact using Marketing, Entrepreneurship and Talent, TEMSMET 2023

作者： Gudodagi, Raveendra Thirumala Akash, K. Ahmed, Mohammed Riyaz REVA University School of Electronics and Communication Engineering Bangalore560064 India

ISBN: (纸本)9798350397819

The idea that DNA encodes the human body is uncontested. Everything about a person, including behaviour and physical characteristics, is influenced by genetic information. Genomic data is a rich source of information when it is analysed, genomic data has a significant potential for use in disease diagnosis. Despite the fact that One size does not fit all, the medical advice is usually generic. The intelligent machine may provide us with additional human body knowledge on the contrary to build intelligent robots. The ongoing development of genomic data is either beneficial for engineering as well as medical research. Our search for personalised medicine may have a solution in the overlapping fields of engineering and medicine. The introduction of new emergent multimedia applications with an increase in demand and consumption of genetic data, as well as the invasion of digital media into every aspect of diagnosis and prognosis, are compelling new challenges for next-generation sequencing. The processing of genomic data is intended to meet hitheito unrecognised requirements, including compression, robustness, security, unambiguity, and the prediction of future anomalies, in addition to delivering individualised treatment. Deep neural network based deep learning has been intensively researched in recent years as one of the possible methods for overcoming these difficulties. Because digital data must be maintained effectively, with very high quality, and shouldn't be easily modified by computer standards. The goal is to develop a safe genome compression method that significantly outperforms existing sequencing methods in terms of all performance parameters. © 2023 IEEE.

关键词： Digital storage

来源：评论

学校读者我要写书评

暂无评论

An Effective and Real-time Time-Slot Power Detection Method 3

An Effective and Real-time Time-Slot Power Detection Method

引用

3rd international conference on Electronic InformationTechnology and Smart Agriculture, ICEITSA 2023

作者： Zhang, Xian Luo, Xinhui Qu, Taiguo Yin, Dong Huaihua University Hunan Huaihua418000 China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua University Huaihua418000 China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua University Hunan Huaihua418000 China Department of Art Design Huaihua Tourism School Hunan Huaihua418000 China

ISBN: (纸本)9798400716775

To efficiently detect the time-slot power of the Time Division Multiple Access (TDMA) communication systems such as repeaters and base stations in real-time. This article designs a signal-sampling hardware circuit based on the Advanced RISC Machine (ARM) platform and proposes a comprehensive method to calculate the time-slot power values. The signal sampling circuit uses the ADC108S052 chip with an 8-channel linked to the ARM via the Serial Peripheral Interface (SPI), and the time-slot power detection approach consists of a signal timing sampling module, sampling data reading module, and sampling data processing module to compute the detected time-slot power comprehensively. We design experiments to evaluate the efficacy of the approach to detect the time-slot power with the system power-on and normality running condition, the detection of the system CPU resource consumption for the time-slot power, the detection of the error value for the time-slot power, etc. The experimental results demonstrate that the approach can be efficient, and real-time detection of the time-slot power of the TDMA system, the system of repeaters and base stations and other systems of signal coverage, optimization and so on is of great significance. © 2023 ACM.

关键词： signal sampling

来源：评论

学校读者我要写书评

暂无评论

Investigating and Implementing the Efficiency of Image Restoration Techniques in Digital Image processing 3

Investigating and Implementing the Efficiency of Image Resto...

引用

3rd international conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Acharjya, Kalyan Yuvaraj, S. Jadhav, Varsha D. Sidhu, Amritpal Sinha, Deepak Kumar Kaneria, Ojasvee Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Computer Science and Engineering Faculty of Engineering and Technology Karnataka Bangalore India Vivekananda Global University Department of Computer Science & Engineering Jaipur India

ISBN: (纸本)9798350319125

This look at explores the efficiency of diverse photo recovery strategies, inclusive of noise reduction, histogram change, facet enhancement, polishing, and smoothing, in digital picture processing. An extensive evaluation of the techniques becomes conducted to assess their effectiveness in restoring degraded virtual pictures. Numerous objective metrics, together with Structural Similarity (SSIM) Index, peak sign-to-Noise Ratio (PSNR), and mean Squared blunders (MSE), have been used to quantitatively examine the first-rate of the restored photographs. Effects indicated that noise discount and area enhancement furnished the finest improvements within the snap shots. Histogram changes and sprucing also stepped forward the high-quality of the pictures, at the same time as the smoothing technique ended in a moderate lower in pleasant. This examines offers a detailed insight into the efficiency of various photo healing techniques and can serve as a reference for in addition investigations. © 2023 IEEE.

关键词： Investigations Smoothing Strategies Structural Techniques

来源：评论

学校读者我要写书评

暂无评论

Garbage Recycling using Machine Learning Techniques 3

Garbage Recycling using Machine Learning Techniques

引用

3rd international conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023

作者： Padmakala, S. Saveetha Institute of Medical and Technical Science Saveetha School of Engineering Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350343632

The term 'garbage recycling' was coined to describe the laborious process of data preparation that is essential to the success of machine learning when it comes to training and evaluating models. data cleansing is the process of removing outliers from a dataset, such as those that are irrelevant, duplicate, noisy, or incorrect. Here, the objective is to collect data that is both accurate and comprehensive so that machine learning algorithms can perform better and generalize more effectively. data Collection is one of the most important phases of garbage recycling in ML. Incorporating any noise and discrepancies from data collection from multiple sources. Cleansing data using methods like imputation, filtering, and outlier detection to deal with problems like missing data, extreme values, and noise. Scaling and normalizing data as part of data Transformation Engineering helps keep things looking consistent and comprehensible. De-duplicating data Locating and erasing redundant information helps reduce prejudice and unnecessary effort. Harmonization of the data Taking into account class imbalances when solving classification problems in order to eliminate model bias. data Splitting is the process of precisely evaluating the performance of a model by dividing the dataset into training, validation, and test sets. Monitoring the data's quality involves keeping an eye on it at all times and ensuring that it remains consistent. monitoring changes and keeping a record of previous versions of datasets in order to ensure reproducibility. This results in more dependable and accurate predictions across a variety of applications. The accurate preparation of data continues to serve as an essential building block for the accomplishment of Machine Learning (ML) models. © 2023 IEEE.

关键词： CNN data Cleaning data processing data Deduplication data Imputation data Transformation Feature Selection Noise Reduction

来源：评论

学校读者我要写书评

暂无评论

FPGA Implementation of Rate Matching in 5G NR PDSCH 38

FPGA Implementation of Rate Matching in 5G NR PDSCH

引用

38th IEEE Region 10 conference, TENCON 2023

作者： Jain, Rochak Anjum, Naveed Soujanya, Samudrala Rudramuniyappa, Harsha Jain, Aviral Bisht, Ashutosh Sharma, Ekant Singh, Prem Iit Roorkee Department of Ece India IIIT Bangalore Department of Ece India

ISBN: (纸本)9798350302196

5G new radio (NR) distinguishes itself by offering remarkable features such as significantly higher throughput and lower latency compared to 4G. In 5G, low density parity check (LDPC) encoding is employed as the channel coding scheme for the transmission of data bits. Subsequent to the LDPC encoding stage, bit selection and bit interleaving operations are performed. Rate matching plays an important role in selecting specific encoded bits for transmission, utilizing techniques like shortening and repetition to support hybrid automatic repeat request functionality. To address the issue of latency encountered in processing large transport blocks, we propose parallel algorithms for the rate matching. These algorithms are implemented on field programmable gate arrays, and then the performance of the optimized algorithms is compared with the existing algorithms specified in the 3rd generation partnership project standards. © 2023 IEEE.

关键词： signal encoding

来源：评论

学校读者我要写书评

暂无评论

Ergodicity and Mixing of Conditional Linear Random Processes in the Problems of Information signal Modelling and Analysis 3

Ergodicity and Mixing of Conditional Linear Random Processes...

引用

3rd international Workshop on Information Technologies: Theoretical and Applied Problems, ITTAP 2023

作者： Fryz, Mykhailo Kharchenko, Serhii Scherbak, Leonid Ternopil Ivan Puluj National Technical University Ruska st. 56 Ternopil46001 Ukraine General Energy Institute of NAS of Ukraine Antonovycha st. 172 Kyiv03150 Ukraine

Ergodicity is a fundamental property in statistical information signal modelling and processing because it simplifies the analysis and estimation of signal properties and system parameters. It enables practitioners to work with single realizations of signals and make meaningful statistical inferences, which is necessary when dealing with real-world data and signals. The continuous-time stationary conditional linear random process as a mathematical model of information signals has been analyzed in the paper using characteristic functions method. The mixing property of the process, from which its ergodicity follows, has been proven. © 2023 CEUR-WS. All rights reserved.

关键词： Random processes

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共296页 << < 62 63 64 65 66 67 68 69 70 71 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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：