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
6,247 篇 期刊文献
3 篇 学位论文
1 册 图书

馆藏范围

43,563 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

14,599 篇 工学
- 9,922 篇 电气工程
- 3,761 篇 计算机科学与技术...
- 2,942 篇 信息与通信工程
- 1,602 篇 控制科学与工程
- 1,549 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
- 393 篇 测绘科学与技术
- 359 篇 航空宇航科学与技...
- 334 篇 生物医学工程（可授...
- 147 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
2,663 篇 理学
- 1,245 篇 物理学
- 904 篇 系统科学
- 308 篇 数学
- 157 篇 地球物理学
- 55 篇 化学
- 44 篇 生物学
789 篇 医学
- 567 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

43,563 篇 signal processin...
8,932 篇 signal processin...
5,935 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...
2,769 篇 hardware
2,447 篇 convergence
1,787 篇 array signal pro...
1,698 篇 feature extracti...
1,647 篇 optimization
1,610 篇 computer archite...
1,596 篇 signal to noise ...
1,523 篇 robustness
1,485 篇 adaptive filters
1,463 篇 vectors

机构

46 篇 school of inform...
44 篇 department of el...
43 篇 national mobile ...
38 篇 department of el...
38 篇 xidian univ natl...
35 篇 information syst...
34 篇 philips research...
31 篇 univ chinese aca...
31 篇 beijing inst tec...
31 篇 school of electr...
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

42,331 篇 英文
992 篇 其他
236 篇 中文

检索条件"主题词=Signal Processing Algorithms"

共 43563 条记录，以下是4581-4590 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：

Cotton Jassid Infestation Monitoring Using Sentinel-2 MSI, Landsat 9 TIRS, and PlanetScope Imagery with Machine Learning and Data Fusion

Cotton Jassid Infestation Monitoring Using Sentinel-2 MSI, L...

引用

International Conference on Computer and Applications (ICCA)

作者： Souleymane Bah M. D. Tanguy Mesreil Houegbe Emmanuel Wilfried G. Megnigbeto Vinasetan Ratheil Houndji Bignon Nicanor Kouton N. Gérard Gouwakinnou C. Eugène Ezin Institut de Mathématiques et de Sciences Physiques Université d'Abomey-Calavi Dangbo Bénin BiPLAC Laboratoire d'Ecologie de Botanique et de Biologie végétate Parakou Benin Division protection phytosanitaire Institut de Recherche sur le Coton Parakou Bénin Institut de Formation et de Recherche en Informatique Université d'Abomey-Calavi Abomey-Calavi Benin

ISBN: (数字)9798350367560

ISBN: (纸本)9798350367577

The excessive use of synthetic pesticides in the fields is the cause of numerous problems to human health and biodiversity. Knowing the location and severity of the emergence of pests enables targeted treatment, helping to reduce the use of pesticides. Given that traditional field inspection requires considerable effort with limited effectiveness, remote sensing combined with machine learning is an essential complement for large-scale, efficient monitoring. This study therefore aims to develop a machine learning-based solution for detecting cotton jassids from free satellite imagery data in Alibori, northern Benin. Multispectral and thermal infrared images respectively from the Sentinel-2 and Landsat 9 satellites were fused in the most correlated bands using signal processing algorithms Pseudo Wigner Distribution (PWD), Nonsubsampled Contourlet Transform (NSCT), and Discrete wavelet transform (DWT). Two configurations, in terms of data augmentation, were used. Areas infested by jassids were identified in merged and unmerged satellite images (Sentinel-2, Landsat 9, and PlanetScope, a commercial satellite) using Support Vector Machine (SVM), Random Forest (RF), and CatBoost supervised machine learning algorithms. The green and Thermal Infrared Sensor 1 (TIRS1) bands are the most correlated in configuration 1 and the blue and TIRSI bands in configuration 2 for respectively Sentinel-2 and Landsat 9. The DWT and NSCT signal processing algorithms produced the least Root Mean Square Deviation (RMSE) for image fusion (0.46 for DWT and 0.33 for NSCT). The best result in terms of detecting performance was obtained with the composite treatment of Landsat 9 images and the RF algorithm, with an overall accuracy of 88.23%, an Fl-score of 82%, and a Kappa index of 79.92% in configuration 1 and in configuration 2 for composite treatment of Sentinel-2 an overall accuracy of 92.36%, an Fl-score of 90.75 % and a Kappa index of 86.36% with CatBoost algorithm.

关键词： Radio frequency Support vector machines Satellites Machine learning algorithms signal processing algorithms Landsat Discrete wavelet transforms Satellite images Cotton Monitoring

来源：评论

学校读者我要写书评

暂无评论

signal Optimization and Noise Reduction Based on Frequency Control in Acoustic Imaging Instruments

Signal Optimization and Noise Reduction Based on Frequency C...

引用

International Conference on Information Systems and Computer Aided Education (ICISCAE)

作者： Zuyang Cao Xin Zhang Junkang Bao Hangzhou Crysound Electronics Co. Ltd. Hangzhou Zhejiang China

ISBN: (数字)9798350350760

ISBN: (纸本)9798350350777

Papermaking machinery noise is the noise generated during the production process of a papermaking enterprise, which includes mechanical vibration and low-frequency noise. In the field test of paper-making enterprises, the noise range is 100–120 dB. According to the industry noise standard, the value of the noise can not be greater than 85 dB under the working condition of 8 hours. Therefore, to control the source of the noise, it is necessary to control the noise according to the noise mechanism of the equipment itself and block its propagation path in order to effectively reduce the noise of the factory. Visual acoustic imagers can quickly identify the sound source and introduce corresponding noise reduction measures in line with environmental protection. The aim of this study is to investigate the frequency control based signal optimization and noise reduction methods in acoustic imagers. U sing the Visual Acoustic Imager of CRY2600 series, the authors conducted experiments in mechanical air noise and collision vibration noise environments to evaluate the effects of different noise environments, filter types, dynamic frequency tuning strategies and signal processing algorithms on signal optimization and noise reduction. The results show that both low-pass and high-pass filters are effective in improving the signal-to-noise ratio in a specific frequency range, and the dynamic frequency tuning strategy performs better in improving the signal quality compared to the static tuning strategy. Both wavelet threshold denoising and generative adversarial network denoising algorithms perform well in different noise environments (wavelet threshold denoising improves the signal strength from 50dB to 70dB in a mechanical air noise environment, with a 20dB improvement in the signal-to-noise ratio), significantly improving the signal strength. The research results show that combining multiple noise reduction strategies can effectively improve the overall performance of the acous

关键词： Vibrations Visualization Heuristic algorithms Noise Noise reduction signal processing algorithms Filtering algorithms Acoustics Tuning Optimization

来源：评论

学校读者我要写书评

暂无评论

Multiscale Graph Construction Using Non-Local Cluster Features

Multiscale Graph Construction Using Non-Local Cluster Featur...

引用

IEEE Workshop on Machine Learning for signal processing

作者： Reina Kaneko Hayate Kojima Kenta Yanagiya Junya Hara Hiroshi Higashi Yuichi Tanaka Osaka University Japan Tokyo University of Agriculture and Technology Japan

ISBN: (数字)9798350372250

ISBN: (纸本)9798350372267

This paper presents a multiscale graph construction method using both graph and signal features. Multiscale graph is a hierarchical representation of the graph, where a node at each level indicates a cluster in a finer resolution. To obtain the hierarchical clusters, existing methods often use graph clustering; however, they may ignore signal variations. As a result, these methods could fail to detect the clusters having similar features on nodes. In this paper, we consider graph and node-wise features simultaneously for multiscale clustering of a graph. With given clusters of the graph, the clusters are merged hierarchically in three steps: 1) Feature vectors in the clusters are extracted. 2) Similarities among cluster features are calculated using optimal transport. 3) A variable k-nearest neighbor graph (V $k$ NNG) is constructed and graph spectral clustering is applied to the V $k$ NNG to obtain clusters at a coarser scale. Additionally, the multiscale graph in this paper has non-local characteristics: Nodes with similar features are merged even if they are spatially separated. In experiments on multiscale image and point cloud segmentation, we demonstrate the effectiveness of the proposed method.

关键词： Point cloud compression Image segmentation Machine learning algorithms Image resolution signal processing algorithms Machine learning Nearest neighbor methods Feature extraction Vectors signal resolution

来源：评论

学校读者我要写书评

暂无评论

Moth-Flame Optimization for Improving UWSNs Performance

Moth-Flame Optimization for Improving UWSNs Performance

引用

Communication, Computing and signal processing (IICCCS), IEEE International Conference on

作者： Kassem Al-Attabi Suvidha Aswini E Anil Pratap Singh G.Maheswari Rajat Kumar Dwibedi Department Of Computers Techniques Engineering College Of Technical Engineering The Islamic University Najaf Iraq Department Of Computers Techniques Engineering College Of Technical Engineering The Islamic University Of Al Diwaniyah Al Diwaniyah Iraq Department of Computer Application Chandigarh Engineering College Chandigarh Group of Colleges Mohali Punjab India Prince Shri Venkateshwara Padmavathy Engineering College Chennai India Department of Computer Science & Engineering IES Institute of Technology and Management IES University Bhopal M.P. India Department of Information Technology Hindustan Institute of Technology and Science Chennai India Department of ECE Aarupadai Veedu Institute of Technology Vinayaka Mission’s Research Foundation (Deemed to be University) Chennai Tamil Nadu India

ISBN: (数字)9798350390759

ISBN: (纸本)9798350390766

This study aims to examine Moth-Flame Optimization (MFO) algorithm by proposing the use in improving the UWSNs system. UWSNs are indispensable for numerous underwater applications; nevertheless, they are confronted with several crucial hindrances, for example, bandwidth constraint, high-latency communication, and limited energy. Since these are complex problems, optimizing them using various techniques Presents a big challenge that could be addressed by bio-inspired optimization algorithms such as the MFO. The motivation for the development of MFO, which emulates the flight pattern moths for navigation, is to aid in the determination of optimal node positioning, routing path, and energy usage in the case of UWSNs. MATLAB workflow includes data collection, algorithm customization, and simulation and forms the basis of the overall methodology applied in the study. A comparison is made with regards to parameters such as network lifetime, energy utilization, data transmission success rate and delay using criteria such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The performance comparisons made between the proposed MFO algorithm and the traditional GA and PSO algorithms prove MFO to be highly effective attaining higher values for all the considered parameters. Thereby, the results demonstrate that the use of MFO has significant promise for increasing the UWSNs lifetime and reliability, making the technique more suitable for underwater surveillance and investigation. It is important for interested researchers and practitioners to understand how some of these bio-inspired optimization techniques can be employed in complex scenarios such as UWSNs, and how this research can inform future work in this area.

关键词： Wireless communication Wireless sensor networks signal processing algorithms Routing Telecommunication computing Reliability Time factors Particle swarm optimization Optimization Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Sentiment Analysis: A Machine Learning Perspective

Sentiment Analysis: A Machine Learning Perspective

引用

Electronics, Communication and signal processing (ICECSP), International Conference on

作者： Nadimpalli Madana Kailash Varma Sri Harsh Mattaparty Shifa Ismail Joel Thaduri Gagan Deep Arora AnandKumar B Department of Artificial Intelligence & Machine Learning Vardhaman College of Engineering Hyderabad Telangana India Department of Information Technology Vardhaman College of Engineering Hyderabad Telangana India Department of Artificial Intelligent & Machine Learning Vardhaman College of Engineering Hyderabad Telangana India

ISBN: (数字)9798350364590

ISBN: (纸本)9798350375381

An essential part of natural language processing, sentiment analysis makes it possible to automatically extract sentiment from textual input. In this work, we examine how well different machine learning algorithms perform when used to analyze the sentiment of real-time Amazon reviews in the automobile niche. Leveraging a dataset comprising reviews from Amazon users, we employ SVM, KNN, Logistic Regression, and Random Forest algorithms to categorize text sentiment as positive, negative, or neutral. This work evaluates the performance of each algorithm in sentiment analysis tasks using strict evaluation standards and testing. Our findings provide insights into the effectiveness of machine learning approaches for analyzing sentiment in real-time reviews, offering valuable implications for businesses and organizations aiming to leverage customer feedback for decision-making and user experience enhancement.

关键词： Support vector machines Sentiment analysis Logistic regression Machine learning algorithms Reviews Decision making signal processing algorithms Real-time systems Automobiles Random forests

来源：评论

学校读者我要写书评

暂无评论

Edge-Featured Graph Attention Network for Power Control in Cell-Free and D2D Heterogeneous Networks

Edge-Featured Graph Attention Network for Power Control in C...

引用

International Conference on Wireless Communications and signal processing (WCSP)

作者： Dewen Yan Yanpeng Dai Ling Lyu Nan Cheng School of Information Science and Technology Dalian Maritime University Dalian China School of Telecommunications Engineering Xidian University Xi'an China

ISBN: (数字)9798350390643

ISBN: (纸本)9798350390650

Cell-free and device-to-device (D2D) heterogeneous networks can effectively enhance spectral efficiency. However, spectrum reuse among different transmission links leads to severe interference to limit the growth of network capacity. In this paper, we propose a power control algorithm based on graph attention network for interference coordination in cell-free and D2D heterogeneous networks. Specifically, a heterogeneous graph is utilized to model the power control problem, where desirable transmissions and interference are represented as edges of different types. The edge-featured attention mechanism is applied over the constructed graph to capture the relationships among various edges. Simulation results show that our proposed algorithm can improve network capacity and exhibit generalization performance with respect to network scales.

关键词： Wireless communication Attention mechanisms Spectral efficiency Simulation Power control signal processing algorithms Interference signal processing Heterogeneous networks Device-to-device communication

来源：评论

学校读者我要写书评

暂无评论

Machine Learning Isolation Forest-Based Target Detection Algorithm for Airborne Radar

Machine Learning Isolation Forest-Based Target Detection Alg...

引用

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

作者： Jing Liu Cao Zeng Filbert H. Juwono Pengcheng Huang Haihong Tao National Key Laboratory of Radar Signal Processing Xidian University Xi’an China Department of Electrical and Electronic Engineering Xi'an Jiaotong-Liverpool University Suzhou China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

While the advantages of airborne radar are widely recognized, it is prone to target overwhelm by clutter during detection tasks, and most traditional detectors rely on clutter mathematical models to obtain detection thresholds. This paper proposes a new machine learning isolation forest-based airborne radar target detection algorithm, fully exploiting the advantages of ensemble decision trees. The proposed algorithm first designs new feature data with feature extraction and space-time weight vector, and the new data enable separate utilization of multidimensional features, serving as inputs for the target and clutter classifier to be constructed. Then, the proposed algorithm designs a unique isolation forest-based target and clutter detector, constructing isolation forest anomaly scores for each designed feature data, and determining the presence of targets for airborne radar based on score discrimination criteria. Compared with various classical detectors, the proposed algorithm significantly enhances target detection performance, providing higher detection probabilities, and offering a new idea and direction for radar target detection. The proposed algorithm is confirmed by simulations to be effective and advantageous.

关键词： Machine learning algorithms Airborne radar signal processing algorithms Forestry Object detection Detectors Machine learning Feature extraction Classification algorithms Clutter

来源：评论

学校读者我要写书评

暂无评论

Video Group Activity Recognition Based On Multidimensional Spatio-Temporal Relationships

Video Group Activity Recognition Based On Multidimensional S...

引用

International Conference on signal processing Proceedings (ICSP)

作者： Yanshan Li Hailin Zong Suixuan He Miaomiao Wei Institute of Intelligent Information Processing Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen China

ISBN: (数字)9798350387384

ISBN: (纸本)9798350387391

Spatio-temporal relationships play an important role in group activity recognition. The spatio-temporal relationships are complex and varied, containing relationships between individuals, between individuals and subgroups, and between subgroups. However, there is no unified method for measuring these multidimensional spatio-temporal relationships. Therefore, this paper proposes a set of metric methods for multidimensional spatio-temporal relationships based on geometric algebra, including the metric method based on positional features and the metric method based on appearance features. And this paper proposed a deep network for video group activity recognition based on multidimensional spatio-temporal relationships. The experimental results show that the proposed algorithm can effectively improve the accuracy of group activity recognition.

关键词： Measurement Accuracy Algebra signal processing algorithms Activity recognition signal processing Spatiotemporal phenomena

来源：评论

学校读者我要写书评

暂无评论

Adaptive Beamforming in MIMO Systems Using Deep Learning

Adaptive Beamforming in MIMO Systems Using Deep Learning

引用

Communication, Computing and signal processing (IICCCS), IEEE International Conference on

作者： Vinithra Banu.T Layth Hussein Varsha Grover T. Arun Kumar Rupesh Sharma I. Sudha Prince Shri Venkateshwara Padmavathy Engineering College Chennai India Department Of Computers Techniques Engineering College Of Technical Engineering The Islamic University Najaf Iraq Department Of Computers Techniques Engineering College Of Technical Engineering The Islamic University Of Al Diwaniyah Al Diwaniyah Iraq Department of Computer Application Chandigarh Engineering College Chandigarh Group of Colleges Mohali Punjab India Department of CSE Kongu Engineering College Department of Electronics & Communication Engineering IES Institute of Technology and Management IES University Bhopal M.P. India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India

ISBN: (数字)9798350390759

ISBN: (纸本)9798350390766

One of the most significant procedures in MIMO system is the adaptive beamforming which is the technique of adjusting the direction of signal transmission for better wireless communication. This paper aims to investigate the application of deep learning in combination with adaptive beamforming for the improvement of the existing technologies and techniques having some limitations which prove efficient when working in certain applications and scenarios only. Utilizing the CNNs and RNNs, the proposed approach then determines ideal beamforming patterns from various datasets, synthetic simulations, as well as measured ones. In this paper, various approaches are employed which include the Super & Reinforcement learning techniques, which makes the deep learning-based models capable of learning in real-time the change of channel characteristics. Simulations and practical adaptations of changing protocols have illustrated substantial enhancements on SINR, BER, and system capacity. The conclusion indicates that the proposed DL based technique is better than the existing standards providing more considerably higher data rates with reasonable less error rates and possessing highly adaptive capability. From the literature, it is clear that deep learning has a significant use in adaptive beam forming; although it has significantly increased the computational load. For future wireless communication technologies such as 5G and beyond MIMO systems this work has demonstrated the promises of deep learning to improve such systems.

关键词： Deep learning Adaptation models Analytical models Adaptive systems Array signal processing Computational modeling Heuristic algorithms signal processing algorithms Standards signal to noise ratio

来源：评论

学校读者我要写书评

暂无评论

Delta Wave Detection Method of Wolff-Parkins on-White Syndrome Based on Electrocardiogram

Delta Wave Detection Method of Wolff-Parkins on-White Syndro...

引用

International Conference on Telecommunications and signal processing (TSP)

作者： Laura-Ioana Mihăilă Paul Faragó Sorin Hintea Bases of Electronics Department Technical University of Cluj-Napoca Cluj-Napoca Romania

ISBN: (数字)9798350365597

ISBN: (纸本)9798350365603

The main indicator in an Electrocardiogram (ECG) signal that marks the existence of Wolff-Parkins on-White (WPW) syndrome is the slurred upstroke. This index is called the Delta wave and appears on the signal morphology due to the existence of a pathological conduction pathway from the atria to the ventricles. Therefore, during ventricular activity, a QRS complex with modified morphology will result. This paper presents a new Delta wave detection algorithm based on the ECG signal. The proposed method is based on analysis of the QRS complex to accurately identify the location of the Delta waves. The identification technique consists in the implementation of a detection algorithm by analyzing the slurred upstroke between the Q and R peaks. In the last step, an additional check is performed based on the area of a portion of the R wave and the duration of the QRS complex. This step has the role to determine whether the identified Delta wave is representative of the preexcitation pattern. The algorithm was tested on 48 samples of ECG signals that were retrieved from two databases from the PhysioN et platform. The samples tested contain normal heartbeats and Wolff-Parkins on-White pathology. The purpose of these signals is to evaluate the robustness of the proposed algorithm. After testing the proposed method, the accuracy obtained is 100%. Testing was also performed on a signal that was not annotated with preexcitation syndrome, but it was mentioned that its morphology resembled Wolff-Parkins on-White pathology. In this case, Delta waves were identified on all 8 samples analyzed. Therefore, the proposed method for detecting Delta waves based on the ECG signal provides 1 00% accuracy, demonstrating superior effectiveness in distinguishing abnormal R waves from normal ones in the context of WPW detection.

关键词： Pathology Accuracy Heart beat signal processing algorithms Morphology Electrocardiography Robustness

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 << < 455 456 457 458 459 460 461 462 463 464 > >>

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：