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

3,413 篇 会议
54 篇 期刊文献
20 册 图书

馆藏范围

3,487 篇 电子文献
2 种 纸本馆藏

日期分布

学科分类号

1,651 篇 工学
- 819 篇 电气工程
- 716 篇 计算机科学与技术...
- 509 篇 信息与通信工程
- 388 篇 控制科学与工程
- 377 篇 软件工程
- 179 篇 仪器科学与技术
- 170 篇 电子科学与技术（可...
- 91 篇 机械工程
- 77 篇 生物医学工程（可授...
- 55 篇 材料科学与工程（可...
- 50 篇 光学工程
- 49 篇 测绘科学与技术
- 42 篇 航空宇航科学与技...
- 39 篇 交通运输工程
- 34 篇 生物工程
- 27 篇 化学工程与技术
- 20 篇 动力工程及工程热...
- 20 篇 土木工程
- 18 篇 安全科学与工程
597 篇 理学
- 346 篇 物理学
- 206 篇 数学
- 62 篇 系统科学
- 43 篇 生物学
- 39 篇 统计学（可授理学、...
- 29 篇 化学
195 篇 管理学
- 164 篇 管理科学与工程(可...
- 35 篇 图书情报与档案管...
193 篇 医学
- 173 篇 临床医学
- 39 篇 基础医学(可授医学...
- 19 篇 药学(可授医学、理...
14 篇 教育学
9 篇 法学
8 篇 军事学
5 篇 经济学
5 篇 农学
4 篇 文学
2 篇 艺术学

主题

1,680 篇 signal processin...
548 篇 signal processin...
488 篇 estimation
475 篇 field programmab...
425 篇 ofdm
424 篇 modulation
424 篇 clocks
393 篇 filtration
274 篇 digital signal p...
173 篇 algorithm design...
158 篇 array signal pro...
154 篇 signal to noise ...
143 篇 feature extracti...
139 篇 hardware
122 篇 accuracy
106 篇 image processing
103 篇 real-time system...
98 篇 computer archite...
71 篇 testing
69 篇 wireless communi...

机构

21 篇 tianjin key labo...
16 篇 tianjin key lab ...
12 篇 lovely professio...
8 篇 university of ch...
7 篇 cuny ny 10021 us...
7 篇 school of inform...
7 篇 the center for a...
7 篇 harbin inst tech...
6 篇 centre of resear...
6 篇 advanced technol...
6 篇 advanced signal ...
6 篇 tianjin key labo...
6 篇 institute of aer...
5 篇 department of el...
5 篇 us dept def ft g...
5 篇 beijing key labo...
5 篇 school of inform...
5 篇 michigan state u...
5 篇 institute of aco...
4 篇 shanghai advance...

作者

23 篇 renbiao wu
12 篇 cohen l
11 篇 andrzej cichocki
10 篇 joohwan chun
9 篇 m.a. bayoumi
8 篇 cichocki andrzej
7 篇 a. cichocki
7 篇 dan lu
7 篇 yao k
6 篇 ebrahimi touradj
6 篇 in-cheol park
6 篇 liu hong
5 篇 sangarapillai la...
5 篇 liu yang
5 篇 nelson dj
5 篇 zhigang su
5 篇 anon
5 篇 qingyan shi
5 篇 junfeng li
5 篇 amin mg

语言

3,425 篇 英文
46 篇 中文
18 篇 其他
1 篇 土耳其文

检索条件"任意字段=Conference on Advanced Signal Processing Algorithms"

共 3487 条记录，以下是351-360 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：

Efficient Approach for Epileptic Seizure Classification and Detection based on Genetic Algorithm with CNN-RNN Classifier

Efficient Approach for Epileptic Seizure Classification and ...

引用

Advances in Computing, Communication and Applied Informatics (ACCAI), International conference on

作者： R. Priyanka M. Sathesh T Tamil Selvi P. Janardhan Saikumar K Venkatachalam M. Raja Department of Networking and Communications College of Engineering and Technology School of Computing SRM Institute of Science and Technology KTR Campus Chengalpattu India Department of ECE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu India Department of Electronics and Instrumentation Engineering Sri Sai Ram Engineering College Chennai Tamil Nadu India Department of ECE Audi Sankara College of Engineering & Technology Gudur India Department of Electronics and Communication Engineering Audi Sankara College of Engineering and Technology Gudur India Department of ECE Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai Tamilnadu

ISBN: (数字)9798350389449

ISBN: (纸本)9798350389456

One of the most physically and psychologically damaging neurological conditions that affect people of all ages is an epileptic seizure. The abnormality should be recognized early so that the proper treatment is timely. It is possible only with advanced signal processing techniques to distinguish and predict epileptic patterns in which substantial effort is invested. Therefore, efficient seizure detection and classification methods are proposed for machine learning and deep learning algorithms. The proposed method uses deep and machine-learning algorithms for seizure detection and classification. The objective is to analyze the performance and efficiency of deep and machine learning classifiers by comparing the various classifiers. This proposed work uses 11,500 EEG data samples from the UCI machine learning repository. To suggest an Improved Fitness Function Genetic Algorithm (IGA) technique for optimal feature selection to improve the detection rate and CNN-RNN algorithm used as the classifier. The analysis proved that the hybrid CNNRNN(LSTM with GRU) classifier with GA-based feGAbased-lection provides better densification accuracy results of 98% when compared with all other classifiers.

关键词： Machine learning algorithms Accuracy signal processing algorithms signal processing Prediction algorithms Brain modeling Classification algorithms

来源：评论

学校读者我要写书评

暂无评论

SAR Target Recognition Preprocessing Based on Reconfigurable Computing Architecture

SAR Target Recognition Preprocessing Based on Reconfigurable...

引用

IEEE International conference on Information Communication and signal processing (ICICSP)

作者： Mengxiang Li Yongxiang Li Han Fang China Telecom Corporation Ltd. Beijing China

ISBN: (数字)9798350355895

ISBN: (纸本)9798350355901

Synthetic aperture radar (SAR) is widely used in various military and civilian fields due to its advantages such as high resolution, strong penetration and all-weather working ability. With the development of SAR imaging technology, the quantity of SAR image data continues to increase, which puts higher requirements on data processing capabilities. Moreover, the lightweight and miniaturized design of radar systems is the future development trend. Traditional computing models can no longer meet the above development needs, and new solutions are urgently needed. The SAR raw image contains a large amount of coherent speckle noise, which requires preprocessing to ensure the accuracy of subsequent target recognition. In order to solve the above problems, this paper implements the preprocessing of SAR target recognition based on coarse-grained reconfigurable array (CGRA). Experimental results show that compared with the implementation based on the most advanced FPGA, the proposed architecture has greatly improved energy efficiency.

关键词： Accuracy Target recognition Fast Fourier transforms Array signal processing Simulation signal processing algorithms Speckle Radar polarimetry Energy efficiency Synthetic aperture radar

来源：评论

学校读者我要写书评

暂无评论

A Method of Sleeping Breathing signal Recognition

A Method of Sleeping Breathing Signal Recognition

引用

Cybersecurity, Internet of Things and Soft Computing (CITSC), Asia-Europe conference on

作者： Cai Chen Ningling Zhang Danyang Lv Yunjie Zhang Zhi Li Chongxuan Tian Xiangwei Meng Fulai Peng Fengxia Wu Shandong Institute of Advanced Technology Chinese Academy of Sciences Jinan China Institute of Biomedical Engineering School of Control Science and Engineering Shandong University Jinan China School of Basic Medical Sciences Shandong University Jinan China

ISBN: (数字)9798331504205

ISBN: (纸本)9798331504212

Traditional polysomnography monitoring is complicated and time-consuming, and bracelets and other sleep monitoring devices cannot directly detect respiratory airflow. In this work, we designed a portable sleep monitoring equipment that connects to the forehead and captures data on air flow directly. The sleep monitoring system can gather data from the following modules: blood oxygen, respiration, acceleration sensor, bioelectrical signal collection, and microphone. In addition, this work describes a method for identifying respiratory peak using a dynamic threshold to determine respiratory frequency. Fourteen healthy individuals took part in the investigation, wearing both our portable sleep monitoring equipment and a reference device at night. Due to the obvious phenomenon of baseline drift, the smooth filtering begins after baseline correction. For respiratory events such as oral respiration, apnea, and hypopnea, we set the maximum threshold and minimum threshold update time. The results reveal that the portable sleep monitoring system can accurately identify the breathing peaks.

关键词： Forehead Heuristic algorithms signal processing algorithms Nose signal processing Sleep apnea Internet of Things Wearable devices Monitoring Microphones

来源：评论

学校读者我要写书评

暂无评论

Training Quantum Self-Attention Model in Near-Term Quantum Computer

Training Quantum Self-Attention Model in Near-Term Quantum C...

引用

International conference on Wireless Communications and signal processing (WCSP)

作者： Junyuan He Yin Kan Cheng Xue Institute of Advanced Technology University of Science and Technology of China Hefei China AHU-IAI AI Joint Laboratory Anhui University Hefei China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei China

ISBN: (数字)9798350390643

ISBN: (纸本)9798350390650

Quantum computing is rapidly emerging as a revolutionary computing paradigm with significant development potential. Variational quantum algorithms, especially those employing variational quantum circuits, have demonstrated notable advantages in domains including finance, chemistry, and machine learning. However, the practical deployment of these algorithms on Noisy Intermediate-Scale Quantum (NISQ) devices faces challenges due to quantum noise, state collapse, and limited qubits numbers. The real-world performance of these algorithms remains largely unexplored. This paper addresses this gap by proposing and implementing a novel method for training quantum self-attention model for text classification directly on quantum computing chips. This initiative marks the first instance of employing such models on actual quantum hardware. Our approach optimizes quantum circuit designs to mitigate the impact of quantum noise and introduces parallel training strategies to enhance efficiency. Our experiments, conducted on the “Wukong” superconducting 72-qubit quantum computer, demonstrate that our models can be effectively trained on real quantum hardware. The results from the actual quantum chips slightly outperformed those from simulators, confirming the practical feasibility of applying quantum self-attention model to natural language processing tasks. These results validate the effectiveness of our approach and provide valuable insights for the future deployment of quantum machine learning models.

关键词： Training Quantum computing Machine learning algorithms Computational modeling Machine learning Hardware Natural language processing Classification algorithms Integrated circuit modeling Quantum circuit

来源：评论

学校读者我要写书评

暂无评论

Algorithm for Drone Recognition from Birds Based on a Neural Network Approach Using Radar Data

Algorithm for Drone Recognition from Birds Based on a Neural...

引用

International Youth conference on Radio Electronics, Electrical and Power Engineering (REEPE)

作者： Alexandr R. Gorbunov Marat R. Akmalov Alexey E. Semichastnov Dmitry A. Balakin Department of Radio Engineering Fundamentals National Research University “MPEI” Moscow Russian Federation Radio Engineering Department ETMC EXPONENTA LTD Moscow Russian Federation

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

Unmanned Aerial Vehicles (UAVs) are widely used in civil and military applications, increasing the need for reliable detection to protect critical infrastructure. Radar is an effective method for detecting UAVs at long distances and in all weather conditions. However, the similarity in size between UAVs and birds often leads to false positives, posing a problem in distinguishing between them. This study addresses this problem by proposing a classifier based on the micro-Doppler effect that discriminates between radar signals from UAVs and birds. The classifier uses a neural network approach, achieving an accuracy of more than 90%. The Engee mathematical computing and dynamic modeling environment was used for the computations. This work highlights the potential of advanced signal processing and machine learning to improve UAV detection systems, reduce false alarms, and improve the safety of critical facilities.

关键词： Training Accuracy Laser radar Neural networks signal processing algorithms Radar detection Birds Autonomous aerial vehicles Numerical models Classification algorithms

来源：评论

学校读者我要写书评

暂无评论

A Smart Model to Manage Traffic Using Infrared Sensors and Bell Detection System: A Computer Controlled Traffic System 2

A Smart Model to Manage Traffic Using Infrared Sensors and B...

引用

2nd IEEE International conference on Communication, Security and Artificial Intelligence, ICCSAI 2023

作者： Saxena, Ashendra Kumar Adlin, Jebakumari S. College of Computing Science and Information Technology Teerthanker Mahaveer University Uttar Pradesh Moradabad India University Karnataka Bangalore India

ISBN: (纸本)9798350369960

The escalating challenge of traffic congestion in urban areas necessitates innovative solutions at the intersection of computer science and artificial intelligence. The main problem is in the outdated nature of conventional traffic signal systems, which function based on predetermined time intervals and fail to appropriately adjust to the ever-changing patterns of urban traffic. This study presents a sophisticated traffic management system that utilizes machine learning and data mining concepts to optimize real-time traffic signal regulation. The suggested system utilizes infrared sensors to constantly monitor the level of traffic congestion at crossings. The data is transmitted to an advanced microcontroller, which utilizes machine learning techniques to forecast traffic patterns and subsequently modify the timing of traffic signals. This approach enables a more seamless and adaptable control of traffic flows, resulting in a substantial decrease in congestion and enhancement of overall traffic efficiency compared to traditional systems. By incorporating computer vision techniques, the system's ability to detect and evaluate several traffic parameters, such as vehicle count, speed, and categorization, is improved. The data is essential for the machine learning models to make well-informed recommendations regarding the durations of traffic lights. Furthermore, the system integrates robotics components to physically manipulate and operate traffic light hardware, guaranteeing smooth functioning and immediate response to the computational decisions made by the microcontroller. This research not only addresses the immediate practical concerns of urban traffic management but also contributes to the broader field of AI and robotics in realworld applications. The synergy of data mining, machine learning, and computer vision within a robust traffic management system exemplifies the transformative potential of AI technologies in urban infrastructure management. © 2023 IEEE.

关键词： Audio signal Detection Machine Learning algorithms Real-Time Data processing Traffic Optimization Techniques

来源：评论

学校读者我要写书评

暂无评论

Is Multi-Task Learning an Upper Bound for Continual Learning?

Is Multi-Task Learning an Upper Bound for Continual Learning...

引用

International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Zihao Wu Huy Tran Hamed Pirsiavash Soheil Kolouri Department of Computer Science Vanderbilt University Nashville TN Department of Computer Science University of California Davis CA

Continual learning and multi-task learning are commonly used machine learning techniques for learning from multiple tasks. However, existing literature assumes multi-task learning as a reasonable performance upper bound for various continual learning algorithms, without rigorous justification. Additionally, in a multi-task setting, a small subset of tasks may behave as adversarial tasks, negatively impacting overall learning performance. On the other hand, continual learning approaches can avoid the negative impact of adversarial tasks and maintain performance on the remaining tasks, resulting in better performance than multi-task learning. This paper introduces a novel continual self-supervised learning approach, where each task involves learning an invariant representation for a specific class of data augmentations. We demonstrate that this approach results in naturally contradicting tasks and that, in this setting, continual learning often outperforms multi-task learning on benchmark datasets, including MNIST, CIFAR-10, and CIFAR-100.

关键词： Upper bound Machine learning algorithms Supervised learning signal processing algorithms Self-supervised learning Benchmark testing signal processing

来源：评论

学校读者我要写书评

暂无评论

Review of MRI brain tumor segmentation and MGMT promoter classification methods on BraTs dataset based on Deep learning

Review of MRI brain tumor segmentation and MGMT promoter cla...

引用

International conference on advanced Technologies for signal and Image processing (ATSIP)

作者： Feriel Amor Hiba Mzoughi Ines Njeh Mohamed Ben Slima Advanced Technologies for Image and Signal Processing (ATISP Lab) Sfax University National Engineering School of Sfax ATMS LAB Tunisia Gabès university Higher Institute of Computer Science and Multimedia of Gabes Gabes Sfax University National School of Electronics and Telecommunications of Sfax Sfax

ISBN: (数字)9798350351484

ISBN: (纸本)9798350351491

During clinical decision-making, the segmentation process Is considered an important task because it provides valuable information about the location, size, and characterization of the brain tumor. However, manual human segmentation is error-prone, time-consuming, and requires skilled *** resonance imaging (MRI) could give extremely detailed images for the investigation and diagnosis of glioblastoma brain *** compared evaluated approaches on the BRATS 2021 and BRATS 2022 datasets and found that they outperformed and could compete with state-of-the-art algorithms in comparable *** our research, we focused on two crucial tasks: segmentation and MGMT classification. This study also addresses asn objective evaluation through performance evaluation of cutting-edge DL-based techniques for MR image analysis (Brats 2021-Brats 2022). Based on the findings of the contrasted methods, we can confirm that using a combination of DL techniques will produce more accurate segmentation results than depending on a single, unique methodology. For the second task, five distinct deep learning-based methods were evaluated to predict the methylation state of the MGMT promoter.

关键词： Deep learning Performance evaluation Learning systems Image segmentation Accuracy Reviews Magnetic resonance imaging

来源：评论

学校读者我要写书评

暂无评论

Thinking in Emoticons: A Peek into the Future of Brain-Computer Interaction

Thinking in Emoticons: A Peek into the Future of Brain-Compu...

引用

Software, Systems and Information Technology (SSITCON), International conference on

作者： Mehak Nasheen Aslam S Jayanth Rajeshwari Patil Dept. AI and DS Nitte Meenakshi Institute of Technology Bengaluru India

ISBN: (数字)9798350352931

ISBN: (纸本)9798350352948

This paper presents an investigation into the application of Brain-Computer Interface (BCI) technology for emoji selection by analyzing electroencephalographic (EEG) signals. EEG data was captured to interpret neural activity, with a Support Vector Machine (SVM) classifier employed for accurate emoji recognition. The system demonstrated a classification accuracy of 93.28% while implementing advanced signal processing techniques that reduced noise and improved real-time performance. This research highlights the viability of thought-driven emoji selection and its implications for advancing accessible communication technologies and immersive virtual environments.

关键词： Support vector machines Accuracy Virtual environments signal processing algorithms Software systems Electroencephalography Brain-computer interfaces Real-time systems Vectors Emojis

来源：评论

学校读者我要写书评

暂无评论

A Combined Dispatch Model of Power Load Satisfaction and Comfort Based on Genetic Algorithm

A Combined Dispatch Model of Power Load Satisfaction and Com...

引用

6th International conference on Intelligent Computing and signal processing (ICSP)

作者： Fan Zhang Shan He Xiaoming Lin Yuming Zhao Jianlin Tang Yan Li Electric Power Research Institute of CSG Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Measurement and Advanced Metering Enterprise of Power Grid Guangzhou China Shenzhen Power Supply Co. Ltd. Shenzhen China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

In recent years, the demand for electricity of the whole society has been increasing rapidly, and the power suppliers have been unable to meet the power consumption demand of all users. In order to effectively balance the relationship between the power suppliers and users, and ensure the satisfaction of suppliers and the experience of users, a load optimization model is proposed. Based on Time-of-use tariff, the model comprehensively considers the income satisfaction of the power supplier, the satisfaction of the consumer's electricity expenditure and the satisfaction of electricity consumption, and takes Time-of-use tariff and elastic load as decision variables. Finally, the multi-objective function of residential user price response under Time-of-use tariff mechanism is constructed, and the genetic algorithm is used to optimize the model under various constraints. The experimental results show that the load optimization algorithm can effectively reduce the load curve of residential electricity, and can carry out peak cutting and valley filling on the premise of ensuring the satisfaction of users and power supplier.

关键词： Analytical models Electricity Atmospheric modeling Simulation Tariffs signal processing algorithms Distribution networks Filling Load modeling Genetic algorithms

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349页 << < 32 33 34 35 36 37 38 39 40 41 > >>

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：