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

37,312 篇 会议
6,233 篇 期刊文献
3 篇 学位论文
1 册 图书

馆藏范围

43,549 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

14,584 篇 工学
- 9,908 篇 电气工程
- 3,758 篇 计算机科学与技术...
- 2,936 篇 信息与通信工程
- 1,601 篇 控制科学与工程
- 1,547 篇 仪器科学与技术
- 894 篇 电子科学与技术（可...
- 763 篇 机械工程
- 693 篇 软件工程
- 391 篇 测绘科学与技术
- 359 篇 航空宇航科学与技...
- 333 篇 生物医学工程（可授...
- 145 篇 交通运输工程
- 89 篇 材料科学与工程（可...
- 87 篇 网络空间安全
- 72 篇 石油与天然气工程
- 49 篇 光学工程
- 49 篇 土木工程
- 48 篇 生物工程
- 47 篇 船舶与海洋工程
2,662 篇 理学
- 1,245 篇 物理学
- 904 篇 系统科学
- 308 篇 数学
- 156 篇 地球物理学
- 55 篇 化学
- 44 篇 生物学
788 篇 医学
- 566 篇 临床医学
- 182 篇 基础医学(可授医学...
397 篇 管理学
- 389 篇 管理科学与工程(可...
73 篇 文学
- 73 篇 新闻传播学
73 篇 农学
- 45 篇 作物学
28 篇 军事学
17 篇 艺术学
16 篇 教育学
2 篇 经济学
2 篇 法学

主题

43,549 篇 signal processin...
8,930 篇 signal processin...
5,933 篇 estimation
5,137 篇 field programmab...
4,684 篇 algorithm design...
4,438 篇 clocks
4,379 篇 ofdm
4,104 篇 modulation
3,955 篇 filtration
3,753 篇 digital signal p...
2,767 篇 hardware
2,446 篇 convergence
1,787 篇 array signal pro...
1,696 篇 feature extracti...
1,645 篇 optimization
1,610 篇 computer archite...
1,596 篇 signal to noise ...
1,523 篇 robustness
1,485 篇 adaptive filters
1,460 篇 vectors

机构

46 篇 school of inform...
44 篇 department of el...
43 篇 national mobile ...
38 篇 department of el...
36 篇 xidian univ natl...
35 篇 information syst...
34 篇 philips research...
31 篇 univ chinese aca...
31 篇 school of electr...
30 篇 beijing inst tec...
29 篇 ibm thomas j. wa...
28 篇 department of el...
27 篇 hendisli&#x011f
27 篇 signal processin...
26 篇 department of el...
26 篇 school of comput...
25 篇 department of si...
25 篇 tsinghua univers...
25 篇 school of inform...
24 篇 institute for in...

作者

40 篇 lei wang
37 篇 wei liu
35 篇 jun wang
32 篇 danilo p. mandic
30 篇 p. pirsch
28 篇 k. egiazarian
27 篇 marc moonen
27 篇 eldar yonina c.
26 篇 li li
23 篇 sharon gannot
23 篇 t. kailath
22 篇 ming li
22 篇 walter kellerman...
22 篇 wei li
22 篇 poor h. vincent
21 篇 yui-lam chan
21 篇 jian wang
21 篇 jean-christophe ...
21 篇 christian jutten
21 篇 kailath t

语言

42,319 篇 英文
992 篇 其他
236 篇 中文

检索条件"主题词=signal processing algorithms"

共 43549 条记录，以下是4931-4940 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：

Classification of Moving Ground Targets Using Accelerometer and Microphone Data

Classification of Moving Ground Targets Using Accelerometer ...

引用

IEEE signal processing and Communications Applications (SIU)

作者： İsmail Can Büyüktepe KürŞat İnce Ali Köksal Hocaoğlu DSYSTM HAVELSAN A.Ş. Pendik İstanbul Türkiye Elektronik Mühendisliği Gebze Teknik Üniversitesi Gebze Kocaeli Türkiye

ISBN: (数字)9798350388961

ISBN: (纸本)9798350388978

In this study, an algorithm that can classify people, cars and empty environments was developed using microphone and 3 -axis accelerometer data. k-Nearest neighbor classifier, Support Vector Machine and Decision Tree classifiers were used as classifier models. To solve the problem, sensor data was processed separately and classification was performed. Success analysis was made and it was observed that their performance was limited. In order to increase success, data augmentation and fusion methods have been proposed for classes with different sample numbers. Data preprocessing and feature extraction processes were applied. As a result of the experimental studies conducted with the classifiers used, the proposed data augmentation method and the fusion of two sensor data provided an increase in success in solving the problem.

关键词： Accelerometers Support vector machines signal processing algorithms signal processing Nearest neighbor methods Data augmentation Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Fetal QRS Detection from Single-Channel Abdominal ECG by Adaptive Improved Clustering

Fetal QRS Detection from Single-Channel Abdominal ECG by Ada...

引用

International Workshop on Wearable and Implantable Body Sensor Networks (BSN)

作者： Thinh Nguyen-Quang Tai Le Duc Nguyen Minh Hung Cao Huy-Dung Han School of Electrical and Electronic Engineering Hanoi University of Science and Technology Hanoi Vietnam Department of Biomedical Engineering University of California Irvine Irvine CA USA Department of Electrical Engineering and Computer Science University of California Irvine Irvine CA USA

ISBN: (数字)9798331530143

ISBN: (纸本)9798331530150

Assessment of fetal development and wellness throughout pregnancy is essential in the early detection of pregnancy anomalies. Recent advances in wearable technology have led to the development of home pregnancy monitoring systems, which hold potentials for the continuous monitoring of expectant mothers and their unborn children through fe-tal/maternal electrocardiogram (f/mECG) technology. Given the complexity of extracting useful information from f/mECG data, these devices are often equipped with multiple channels and sophisticated signal processing algorithms. Thus, the implementation of f/mECG monitoring in daily life remains unfeasible. In this study, we propose an algorithm for extracting the fetal electrocardiogram (fECG) using a single channel. The algorithm detects the peaks of the maternal ECG (mECG) through a clustering method, followed by peak correction. The mECG signal is then reconstructed with Principal Component Analysis (PCA) before applying the Template Subtraction (TS) method to obtain fECG. Rigorous testing with various online f/mECG databases demonstrates the potential to accurately extract fECG using only a single channel. The evaluation results based on the online dataset achieved an accuracy of 99.60% and an F1 score of 99.30%. This advancement also opens opportunities to optimize home-based f/mECG monitoring, making it more compact and reliable.

关键词： Pregnancy Measurement Accuracy Fetal heart rate signal processing algorithms Clustering algorithms Filtering algorithms Electrocardiography Monitoring Principal component analysis

来源：评论

学校读者我要写书评

暂无评论

Secrecy Energy Efficiency Maximization for RSMA-Based UAV Communication with Multiple Colluding Eavesdropperse

Secrecy Energy Efficiency Maximization for RSMA-Based UAV Co...

引用

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

作者： Shuzhen Liu Yi Wang Ziheng Sheng Zhiyu Huang Hongwen Yu Zhichao Sheng School of Communication and Information Engineering Shanghai University Shanghai China Key Laboratory of Specialty Fiber Optics and Optical Access Networks Shanghai Institute for Advanced Communication and Data Science Shanghai University Shanghai China The School of Civil and Environmental Engineering UNSW Sydney Australia School of Civil and Environmental Engineering UNSW Sydney Australia

ISBN: (数字)9798350355895

ISBN: (纸本)9798350355901

This paper explores a rate splitting multiple access (RSMA)-based unmanned aerial vehicle (UAV) communication system aimed at enhancing secrecy energy efficiency. An UAV communicates with ground users while multiple colluding eavesdroppers intercept the signals. The secrecy energy efficiency is optimized by designing the RSMA precoding matrix and UAV trajectory, subject to constraints on UAV energy consumption and data requirements. To address the complexity of coupled variables, an iterative algorithm combining the Dinkelbach algorithm and block coordinate descent method is proposed. Simulation results indicate that the secrecy performance of the proposed algorithm outperforms that of the benchmark schemes.

关键词： Simulation Precoding signal processing algorithms Benchmark testing signal processing Autonomous aerial vehicles Energy efficiency Trajectory Iterative methods Optimization

来源：评论

学校读者我要写书评

暂无评论

Breast Cancer Histopathological Image Classification Using CNN and VGG-19

Breast Cancer Histopathological Image Classification Using C...

引用

IEEE International Conference on Intelligent Techniques in Control, Optimization and signal processing (INCOS)

作者： S. Kanimozhi S. Priyadarsini Department of CSE P.S.R Engineering College Sivakasi India

ISBN: (数字)9798350361186

ISBN: (纸本)9798350361193

Applications of deep learning in medicine, like iden- tifying the kind of malignant cells, are common. Breast cancer is a most common type of cancer in women and it a main cause of death for women. There are three categories for the malignant cells: Normal, Mild, and Severe. Early diagnosis of the malignant cells can prevent these deaths. Numerous techniques, including MRIs, mammograms, ultrasounds, and biopsies, are used to identify cancerous cells. Hematoxylin and eosin-stained breast cancer histology photos are difficult to diagnose, labor-intensive, and frequently cause pathologists to disagree. Recent advances in deep learning have made histological image processing possible with convolutional neural networks (CNNs). Histology images of breast cancer are categorized into sub-classes based on general tissue structure and morphology, as well as the density, variabil- ity, and organize of the cells. These subclasses include benign, malignant, and normal. Using this information, extract features at the cell and tissue levels, respectively from histopathological images, in smaller and larger size patches. The dataset repository is where the input image was obtained. The image has to be pre- processed. The feature extraction must then be put into practice. The pre- processed image must then be segmented. The image must be divided. We are able to apply many neural network models, including VGG-19 and Convolutional Neural Network (CNN). The findings of the experiment indicate that the accuracy. The primary goal of our method is to identify or anticipate breast cancer based on the input image.

关键词： Deep learning Training Histopathology signal processing algorithms Feature extraction Prediction algorithms Breast cancer

来源：评论

学校读者我要写书评

暂无评论

Pattern Synthesis of Dual-Polarized Conformal Array Based on Alternating Convex Optimization

Pattern Synthesis of Dual-Polarized Conformal Array Based on...

引用

International Conference on Communications, Circuits and Systems (ICCCAS)

作者： Chao Liu Junjie Qian Tongtao Zhu Xiaoyuan Zhang Lei Zhang Electronics and Communications Engineering Hefei University of Technology Hefei China

ISBN: (数字)9798350386271

ISBN: (纸本)9798350386288

A pattern synthesis of dual-polarized conformal arrays is proposed based on alternating convex optimization. The original beamforming problem is mathematically formulated as a joint optimization problem. However, the presence of both weight and auxiliary phase variables makes the problem non-convex. To address this issue, the non-convex problem is decomposed into two sub-problems, each targeting one variable. The sub-problem for optimizing the auxiliary phase is further transformed into a convex problem by using Taylor expansion. Then an alternating convex optimization approach is applied to iteratively solve the original problem. Furthermore, the “worst point” is identified based on the peak error in the main lobe region. Then the main lobe shaping performance is enhanced by increasing the weight at this point in the iterative process. The validity of method is confirmed by the result of the simulate experiment.

关键词： Array signal processing Circuits and systems Simulation signal processing algorithms Parallel processing Taylor series Convex functions

来源：评论

学校读者我要写书评

暂无评论

Optimization of the SPHINCS+ PQC Algorithm with Custom Instructions and LLVM Integration on a RISC-V Processor

Optimization of the SPHINCS+ PQC Algorithm with Custom Instr...

引用

IEEE signal processing and Communications Applications (SIU)

作者： Mert Paşa Çukur Ece Olcay Güneş Elektronik ve Haberleşme Mühendisliği İstanbul Teknik Üniversitesi Radar ve Elektronik Harp Sistemleri Aselsan Ankara Türkiye Elektronik ve Haberleşme Mühendisliği İstanbul Teknik Üniversitesi İstanbul Türkiye

ISBN: (数字)9798350388961

ISBN: (纸本)9798350388978

With the emergence of quantum computers, traditional open key cryptographic schemes have faced an existential threat that necessitates the development of quantum resistant algorithms. Post Quantum Cryptography (PQC) has emerged as a solution that opposes this new cryptoanalytic evolution with hash based signature schemes such as SPHINCS+, known as one of the leading candidates by NIST. However, SPHINCS+ requires hardware acceleration for practical use. This study offers a method to accelerate the SPHINCS+ algorithm running in the RISC-V processor on the FPGA using the LLVM integration for custom instruction extension. Custom instructions have been developed for the SHA-256 operations, a fundamental component of SPHINCS+, resulting in a 5.09 x acceleration of the algorithm.

关键词： Resistance Computers Quantum computing signal processing algorithms signal processing NIST Quantum cryptography

来源：评论

学校读者我要写书评

暂无评论

Improved BD-EMD Technique using RBF Hermite Interpolation for Image Decomposition

Improved BD-EMD Technique using RBF Hermite Interpolation fo...

引用

Innovations in High Speed Communication and signal processing (IHCSP), International Conference on

作者： Sucheta Bhardwaj Bhupendra Singh Kirar Dheeraj Kumar Agrawal Vivek Patel Sunil Kureel Rahul Yogi Motherson Innovation Germany ECE Department Indian Institute of Information Technology Bhopal India ECE Department Maulana Azad National Institute of Technology Bhopal India Department of CSE IES Institute of Technology and Management Bhopal India

ISBN: (数字)9798350368949

ISBN: (纸本)9798350368956

Presented herein is an enhanced bi-dimensional empirical mode decomposition (BD-EMD) technique incorporating radial basis function with Hermite interpolation (RBF-HI) for image decomposition. Random point interpolation is an integral aspect of BD-EMD. The characteristics of the two-dimensional intrinsic mode functions (2D-IMFs) derived from BD-EMD significantly hinge on the employed interpolation technique. This study systematically examines various interpolation methods, advocating for the adoption of the RBF-HI technique to augment the performance of BD-EMD. Through comprehensive analysis and comparison of diverse interpolation techniques, crucial features of BD-EMD, including precise surface interpolation and image reconstruction, are refined for enhanced optimization. The outcomes attest that the proposed RBF-HI technique outperforms other methods in terms of surface interpolation, demonstrating superior curve fitting and reconstructed image quality. A standard test image of Lena is utilized for performance benchmarking against existing methods. Comparative analysis concludes that the proposed method excels not only in image decomposition but also in image reconstruction. Performance metrics, encompassing processing time, algorithmic complexity, and peak signal-to-noise ratio (PSNR), underscore the efficacy of the proposed method as a superior approach to BD-EMD for image analysis.

关键词： Interpolation Surface reconstruction Technological innovation PSNR signal processing algorithms Image decomposition Surface fitting Image reconstruction Surface treatment Standards

来源：评论

学校读者我要写书评

暂无评论

Integrated Platform of Underwater Acoustic signal Simulation and Classification

Integrated Platform of Underwater Acoustic Signal Simulation...

引用

International Conference on Advanced Computer Theory and Engineering, ICACTE

作者： Haoliang Zhu Tiantian Guo Limin Yu dept. School of Advanced Technology Xi’ an Jiaotong Liverpool University Suzhou China

ISBN: (数字)9798331539887

ISBN: (纸本)9798331539894

With the increase in marine activities, there is a growing need for efficient and accurate underwater acoustic signal processing techniques. In this study, MATLAB-based graphical user interfaces (GUIs) including Receiver signal Simulation GUI, Database System GUI and signal Classification GUI are developed for simulating, sorting, classifying and visualizing underwater acoustic signals with the aim of improving the efficiency and accuracy of acoustic signal processing. By converting one-dimensional acoustic signals into two-dimensional time-frequency spectrogram, this study applies image classification techniques in underwater acoustic signal processing using convolutional neural networks (CNNs), deep neural networks (DNNs), and random forests (RFs) for signal classification. Experimental results show that these machine learning models are able to effectively classify acoustic signals in a low signal-to-noise ratio environment, with CNN and RF showing particular robustness. In addition, the GUI provides a user-friendly platform that greatly simplifies the complex process of analyzing acoustic data. This study not only demonstrates effectiveness of the algorithms in classifying underwater acoustic signals, but also provides new tools and perspectives for marine science research and related application areas. The future work will explore the integration of more machine learning algorithms and extend the functionality of the GUI to support a wider range of acoustic signal processing applications.

关键词： Radio frequency Machine learning algorithms Accuracy Pattern classification signal processing algorithms Convolutional neural networks Underwater acoustics Graphical user interfaces signal to noise ratio Sorting

来源：评论

学校读者我要写书评

暂无评论

Meta-Learning with Test-Time-Train

Meta-Learning with Test-Time-Train

引用

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

作者： Tianao Wang School of Artificial Intelligence Jilin University Changchun China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

Meta-learning algorithm aim to distill experiences from past tasks to achieve rapid adaptation to new tasks. This approach has seen significant success in recent years. However, meta-learning still performs poorly when facing cross-domain tasks, primarily due to the training domain's task set not always providing effective experiences for the test domain's task set. To address this issue, we propose the Meta-learning with Test-time-train algorithm, which combine Test-time-train technique with meta-learning algorithm to minimize training loss of mixed data, enabling the model to adapt more quickly to unseen task distribution. For the training phase, we advocate for using mixed data from trainset and validation set to fine-tune parameter within the outer loop, allowing the model to proactively adapt to different task feature. For the testing phase, we advocate for using mixed data from validation set and test set to fine-tune parameter within the inner loop, making better prediction for unseen tasks. This method constitutes a direct meta-learning framework that seamlessly integrates with existing meta-learning methods to enhance their performance. Experimental evaluation confirm the effectiveness of the proposed framework, demonstrating state-of-the-art performance across different datasets.

关键词： Metalearning Training Adaptation models Computational modeling signal processing algorithms Data integration signal processing Data models Labeling Testing

来源：评论

学校读者我要写书评

暂无评论

Fire Detection Algorithm Based on Improved YOLOv5s

Fire Detection Algorithm Based on Improved YOLOv5s

引用

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

作者： Xiao Wang Shaopeng Li Peng Yan Xiao Ma Ruju Ni Yulu Wu Institute of Automation Qilu University of Technology (Shandong Academy of Sciences) Jinan China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

Aiming at the problem of low detection accuracy caused by existing image fire detection algorithms when performing model lightweighting, the paper proposes an improved fire detection algorithm for YOLOv5s. YOLOv5 compared other YOLO models, it has stronger adaptability and higher sensitivity in fire detection. Firstly, we introduce null convolution to improve the MobileNetV2 lightweight module and replace the CSPDarknet53 backbone network in YOLOv5s to ensure the detection accuracy and reduce the computational complexity of the fire detection model; secondly, we add the CA attention mechanism in front of the SPPF layer of the backbone network, which increases the attention of the model network to the features of spatial and channel information, and improves the positional relationship of the matching degree; finally, the fire image dataset is built to train the improved YOLOv5s algorithm model and complete the flame image detection. The experimental results show that the improved fire detection algorithm improves the detection accuracy while improving the model computation volume, and its model parameter count is reduced by 2.46M and the detection accuracy is improved by 3.1 %.

关键词： YOLO Adaptation models Solid modeling Accuracy Sensitivity Computational modeling signal processing algorithms Fires Feature extraction Detection 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500页 << < 490 491 492 493 494 495 496 497 498 499 > >>

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：