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

444 篇 期刊文献
205 篇 会议
1 篇 学位论文
1 篇 资讯

馆藏范围

651 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

472 篇 工学
- 261 篇 计算机科学与技术...
- 146 篇 软件工程
- 131 篇 电气工程
- 89 篇 信息与通信工程
- 58 篇 控制科学与工程
- 20 篇 仪器科学与技术
- 20 篇 生物工程
- 18 篇 安全科学与工程
- 17 篇 生物医学工程（可授...
- 16 篇 机械工程
- 16 篇 电子科学与技术（可...
- 12 篇 土木工程
- 12 篇 化学工程与技术
- 9 篇 光学工程
442 篇 理学
- 355 篇 数学
- 347 篇 统计学（可授理学、...
- 49 篇 生物学
- 38 篇 物理学
- 25 篇 系统科学
- 11 篇 化学
- 8 篇 地球物理学
67 篇 管理学
- 40 篇 管理科学与工程(可...
- 15 篇 工商管理
- 15 篇 图书情报与档案管...
- 9 篇 公共管理
50 篇 医学
- 26 篇 临床医学
- 17 篇 基础医学(可授医学...
- 8 篇 公共卫生与预防医...
25 篇 经济学
- 21 篇 应用经济学
15 篇 农学
8 篇 法学
- 8 篇 社会学
4 篇 教育学
3 篇 文学

主题

651 篇 expectation maxi...
20 篇 maximum likeliho...
16 篇 gaussian mixture...
15 篇 parameter estima...
14 篇 expectation-maxi...
13 篇 hidden markov mo...
11 篇 maximum likeliho...
9 篇 system identific...
9 篇 image segmentati...
9 篇 kalman filter
7 篇 mixture models
7 篇 missing data
6 篇 hidden markov mo...
6 篇 channel estimati...
5 篇 multiple models
5 篇 clustering
5 篇 bayesian informa...
5 篇 expectation maxi...
5 篇 em algorithm
4 篇 maximum likeliho...

机构

4 篇 institute of aco...
3 篇 univ alberta dep...
3 篇 imt school for a...
3 篇 school of mathem...
3 篇 school of automa...
3 篇 univ melbourne d...
2 篇 department of au...
2 篇 tsinghua univers...
2 篇 mcmaster univ de...
2 篇 zhongtai securit...
2 篇 zhejiang univ co...
2 篇 northeastern uni...
2 篇 univ so calif in...
2 篇 univ atacama fac...
2 篇 department of ma...
2 篇 vinai research v...
2 篇 jiangnan univ sc...
2 篇 center for machi...
2 篇 univ so calif de...
2 篇 department of ch...

作者

7 篇 huang biao
6 篇 krishnamurthy v
6 篇 orlando danilo
5 篇 hao chengpeng
5 篇 shlezinger nir
5 篇 elliott rj
4 篇 yan linjie
4 篇 doerschuk peter ...
4 篇 schmid luca
4 篇 schmalen laurent
4 篇 raviv tomer
3 篇 osoba osonde
3 篇 kim inyoung
3 篇 yu chengpu
3 篇 paliwal kk
3 篇 ge zhiqiang
3 篇 si xiaosheng
3 篇 pal suvra
3 篇 lei chen
3 篇 kosko bart

语言

538 篇 英文
107 篇 其他
5 篇 中文
1 篇 日文

检索条件"主题词=Expectation Maximization Algorithm"

共 651 条记录，以下是361-370 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：

Maximum-likelihood carrier-frequency synchronization and channel estimation for MIMO-OFDM systems

Maximum-likelihood carrier-frequency synchronization and cha...

引用

Wireless Telecommunications Symposium

作者： Salari, S. Ahmadian, M. Ardebilipour, M. Meghdadi, V. Cances, J. P. KN Toosi Univ Technol Tehran Iran Univ Limoges Limoges France

ISBN: (纸本)9781424406968

In this paper, we propose a new scheme for maximum-likelihood (ML) estimation of both carrier-frequency offset (CFO) and channel coefficients in multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. To reduce the prohibitive complexity of ML estimate, the expectation-maximization (EM) algorithm is employed. From Simulations, it is shown that the accuracy of proposed scheme is close to the Cramer-Rao bound (CRB) for both CFO and channel estimations.

关键词： MIMO communication OFDM modulation channel estimation maximum likelihood estimation Cramer-Rao bound MIMO OFDM carrier frequency offset carrier frequency synchronization channel coefficients expectation maximization algorithm maximum l channel estimation Channel Coefficient carrier frequency offset expectation-maximisation algorithm MIMO communication Cramer-Rao bounds frequency synchronization maximum likelihood estimation maximum likelihood CARRIER FREQUENCY

来源：评论

学校读者我要写书评

暂无评论

No Change, No Gain: Empowering Graph Neural Networks with Expected Model Change maximization for Active Learning 37

No Change, No Gain: Empowering Graph Neural Networks with Ex...

引用

37th Conference on Neural Information Processing Systems (NeurIPS)

作者： Song, Zixing Zhang, Yifei King, Irwin Chinese Univ Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9781713899921

Graph Neural Networks (GNNs) are crucial for machine learning applications with graph-structured data, but their success depends on sufficient labeled data. We present a novel active learning (AL) method for GNNs, extending the Expected Model Change maximization (EMCM) principle to improve prediction performance on unlabeled data. By presenting a Bayesian interpretation for the node embeddings generated by GNNs under the semi-supervised setting, we efficiently compute the closed-form EMCM acquisition function as the selection criterion for AL without re-training. Our method establishes a direct connection with expected prediction error minimization, offering theoretical guarantees for AL performance. Experiments demonstrate our method's effectiveness compared to existing approaches, in terms of both accuracy and efficiency.

关键词： expectation maximization algorithm

来源：评论

学校读者我要写书评

暂无评论

Texture Analysis based on Gaussian Mixture Modeling

Texture Analysis based on Gaussian Mixture Modeling

引用

World Congress on Nature and Biologically Inspired Computing

作者： Sobha, T. Remya, S. Adi Shankara Inst Engn & Technol Dept Comp Sci Kalady 683574 Kerala India Univ Kerala Dept Comp Sci Thiruvananthapuram 695121 Kerala India

ISBN: (纸本)9781424450534

Gaussian mixture modeling is a recent approach in texture analysis and is used to model image textures. Texture is modeled using a mixture of Gaussian distributions, which capture the local statistical properties of the texture. The mixture parameters are estimated using expectation maximization algorithm. This algorithm finds the maximum likelihood estimate of the parameters of an underlying distribution from a given data set when data is incomplete. The paper presents a method of identifying changes as well as new patterns in the image using the Gaussian mixture model parameters. Model parameters of the original image texture are computed. Unexpected patterns in the image are discriminated by using weighted normalized Euclidean distance measure derived from the model parameters.

关键词： Texture analysis Gaussian mixtures expectation maximization algorithm Texture modeling Texture discrimination

来源：评论

学校读者我要写书评

暂无评论

Convergence and Consistency Results in Spectral Clustering and Gaussian Mixture Models

Convergence and Consistency Results in Spectral Clustering a...

引用

作者： Zhao, Ruofei University of Michigan

学位级别：博士

Clustering analysis is a popular technique in statistics and machine learning. Despite its wide use, certain theoretical properties of clustering algorithms are not well-understood. In this dissertation, we investigate two problems concerning the convergence and consistency of clustering algorithms. The first problem is on the uniform consistency of spectral embeddings in spectral clustering and in, more generally, spectral methods. The second problem is on the statistical convergence of the expectation maximization (EM) algorithm on Gaussian mixture models. Specifically, in the first problem, we study the convergence of the spectral embeddings obtained from the leading eigenvectors of certain similarity matrices to their population counterparts. We opt to study this convergence in a uniform (instead of average) sense and highlight the benefits of this choice. Using the Newton-Kantorovich Theorem and other tools from functional analysis, we first establish a general perturbation result for orthonormal bases of invariant subspaces. We then apply this general result to normalized spectral clustering. By tapping into the rich literature of Sobolev spaces and exploiting some concentration results in Hilbert spaces, we are able to prove a finite sample error bound on the uniform consistency error of the spectral embeddings in normalized spectral clustering. In the second problem, we study the convergence behavior of the EM algorithm on Gaussian mixture models with an arbitrary number of mixture components and mixing weights. We show that as long as the means of the components are separated by an amount proportional to the square root of the smaller of the number of components and the dimension, the EM algorithm converges locally to the global optimum of the log-likelihood. Further, we show that the convergence rate is linear and characterize the size of the basin of attraction to the global optimum.

关键词： Gaussian mixture models Spectral embedding Spectral clustering expectation maximization algorithm Thesis

来源：评论

学校读者我要写书评

暂无评论

Em algorithm applied to non-stationary noisy phase signals

Em algorithm applied to non-stationary noisy phase signals

引用

IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Taleb, A Ericsson Radio Syst AB SE-16480 Stockholm Sweden

ISBN: (纸本)0780374029

This paper concerns the application of the EM algorithm for the estimation of the parameters of non-stationary noisy phase mono component signals buried in additive noise. Noisy phase signals are appropriate for modeling real world signals such as radar and communications signals. The maximum likelihood estimator for the signal parameters is explicited. The problem is then formulated as a missing data problem which enables a natural use of the expectation-maximization algorithm. A robust initialization scheme based on non-parametric time-frequency distributions is presented. Experimental results with both real and simulated data show the efficiency of the procedure.

关键词： optimisation maximum likelihood estimation noise time-frequency analysis statistical analysis signal processing frequency modulation EM algorithm nonstationary noisy phase signals expectation maximization algorithm parameter estimation noisy phase mono component signals additive noise radar signals communications signals maximum likelihood estimator MLE signal parameters estimation missing data problem robust initialization nonparametric time-frequency distributions quadratic FM signal amplitude modulation AM simulated data real data

来源：评论

学校读者我要写书评

暂无评论

Robust object tracking algorithm in natural environments

引用

2nd International Conference on Natural Computation (ICNC 2006)

作者： Hu, Shi-qiang Liang, Guo-zhuang Jing, Zhong-liang Hebei Univ Sci & Technol Coll Informat & Elect Shijiazhuang 050054 Peoples R China Shanghai Jiao Tong Univ Inst Informat & Elect Shanghai 200030 Peoples R China

ISBN: (纸本)3540459073

In order to realize robust visual tracking in natural environments, a novel algorithm based on adaptive appearance model is proposed. The model can adapt to changes in object appearance over time. A mixture of three Gaussian distributions models the value of each pixel. An online expectation maximization (EM) algorithm is developed to update the parameters of the Gaussians. The observation model in the particle filter is designed based on the adaptive appearance model. Numerous experimental results demonstrate that our proposed algorithm can track objects well under illumination change, large pose variation, and partial or full occlusion.

关键词： visual tracking adaptive appearance model expectation maximization algorithm particle filter

来源：评论

学校读者我要写书评

暂无评论

Unsupervised algorithm for radiographic image segmentation based on the Gaussian mixture model

Unsupervised algorithm for radiographic image segmentation b...

引用

International Conference on Computer as a Tool (EUROCON 2007)

作者： Mekhalfa, Faiza Nacereddine, Nafaa Goumeidane, Aicha Baya Welding & NDT Res Ctr Image & Signal Proc Lab Cheraga Algeria

ISBN: (纸本)9781424408122

In this paper we study an unsupervised algorithm for radiographic image segmentation, based on the Gaussian mixture models (GMMs). Gaussian mixture models constitute a well-known type of probabilistic neural networks. One of their many successful applications is in image segmentation. Mixture model parameters have been trained using the expectation maximization (EM) algorithm. Numerical experiments using radiographic images illustrate the superior performance of EM method in term of segmentation accuracy compared to fuzzy c-means algorithm.

关键词： weld defect radiographic images image segmentation Gaussian mixture model expectation maximization algorithm fuzzy c-means algorithm

来源：评论

学校读者我要写书评

暂无评论

Randomized and Deterministic Maximin-share Approximations for Fractionally Subadditive Valuations 37

Randomized and Deterministic Maximin-share Approximations fo...

引用

37th Conference on Neural Information Processing Systems (NeurIPS)

作者： Akrami, Hannaneh Mehlhorn, Kurt Seddighin, Masoud Shahkarami, Golnoosh Univ Saarland Max Planck Inst Informat Graduiertenschule Informat Saarbrucken Germany Univ Saarland Max Planck Inst Informat Saarbrucken Germany Tehran Inst Adv Studies Tehran Iran

ISBN: (纸本)9781713899921

We consider the problem of guaranteeing maximin-share (MMS) when allocating a set of indivisible items to a set of agents with fractionally subadditive (XOS) valuations. For XOS valuations, it has been previously shown that for some instances no allocation can guarantee a fraction better than 1/2 of maximin-share to all the agents. Also, a deterministic allocation exists that guarantees 0.219225 of the maximin-share of each agent. Our results involve both deterministic and randomized allocations. On the deterministic side, we improve the best approximation guarantee for fractionally subadditive valuations to 3/13 = 0.230769. We develop new ideas on allocating large items in our allocation algorithm which might be of independent interest. Furthermore, we investigate randomized algorithms and the Best-of-both-worlds fairness guarantees. We propose a randomized allocation that is 1/4-MMS ex-ante and 1/8-MMS ex-post for XOS valuations. Moreover, we prove an upper bound of 3/4 on the ex-ante guarantee for this class of valuations.

关键词： expectation maximization algorithm

来源：评论

学校读者我要写书评

暂无评论

Traffic Speed Forecasting by Mixture of Experts

Traffic Speed Forecasting by Mixture of Experts

引用

14th International IEEE Conference on Intelligent Transportation Systems (ITSC)

作者： Coric, Vladimir Wang, Zhuang Vucetic, Slobodan Temple Univ Philadelphia PA 19122 USA Siemens Res Corp Princeton NJ 08540 USA

ISBN: (纸本)9781457721977

Traffic speed is one of the most important quantities for travel information systems. Accurate speed forecasting can help in trip planning by allowing travelers to avoid the congested routes, either by choosing the alternative routes or by changing the departure time. It is also helpful for traffic monitoring, control, and planning. An important feature of traffic is that it consists of free flow and congested regimes, which have significantly different properties. Training a single traffic speed predictor for both regimes typically results in suboptimal accuracy. To address this problem, a mixture of experts algorithm which consists of two regime-specific linear predictors and a decision tree gating function was developed. A generalized expectation maximization algorithm was used to train the linear predictors and the decision tree. The proposed algorithm was evaluated on a 5-mile stretch of I35 highway in Minneapolis containing 10 single loop detector stations, with prediction horizons ranging from 5 minutes to one hour ahead. Experimental results showed that mixture of experts approach outperforms several popular benchmark approaches.

关键词： Forecasting Linear regression Markov processes Prediction algorithms Regression tree analysis Road transportation decision tree decision tree gating function decision trees expectation maximization algorithm expectation-maximisation algorithm experts algo

来源：评论

学校读者我要写书评

暂无评论

Identification of ARX System Based on Shifted Asymmetric Laplace Distribution 38

Identification of ARX System Based on Shifted Asymmetric Lap...

引用

38th Chinese Control Conference (CCC)

作者： Yu, Miao Zhang, Tianyi Yang, Xianqiang Harbin Inst Technol Res Inst Intelligent Control & Syst Harbin Peoples R China

ISBN: (纸本)9789881563972

The identification of AutoRegressive eXogenous (ARX) model by outliers is addressed in this paper. Shifted(non-centralized) asymmetric Laplace (SAL) distribution and expectation maximization (EM) algorithm are employed to estimate the unknown model parameters. Outliers are common in the signal acquisition process and have a serious impact on data-driven modeling method. In this paper, the probability method is used to solve the problem of outliers. When the noise parameter is regarded as a prior exponential distribution, the model output obeys the SAL distribution which is robust to outliers. The known statistical properties of SAL distribution are applied to calculate the M-step in the EM algorithm and get the iterative parametric formula. The accuracy of the proposed algorithm is verified by a numerical simulation example.

关键词： shifted asymmetric Laplace distribution expectation maximization algorithm autoRegressive eXogenous model

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66页 << < 33 34 35 36 37 38 39 40 41 42 > >>

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：