检索结果-内蒙古大学图书馆

AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Hosseini, Seyedbarzin Botkin, Nikolai Diepolder, Johannes Holzapfel, Florian Tech Univ Munich Inst Flight Syst Dynam Boltzmann Str 15 D-85748 Garching Germany Tech Univ Munich Zentrum Math M6 Boltzmann Str 3 D-85748 Garching Germany

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

Test data for flight system identification and parameter estimation are generated by exciting the dynamic systems under investigation with a set of input signals. It is desired to design the inputs such that the information content in the flight test data is maximized, for a given test run time. This can be achieved by applying optimal control methods, if the model structure and preliminary parameter values are known a priori. Most of the optimal input design methods assume ideal conditions. It is assumed that no uncertainty exists in the model structure, a priori parameter values close to the true values are known and an ideal test environment (e.g. no wind) exists. In this paper, a practical approach to design robust optimal inputs is introduced by enhancing the existing solution methods using generalized Polynomial Chaos. The proposed solution method is tested numerically using a simplified nonlinear model of the aircraft longitudinal motion.

关键词： Flight Vehicle Systems Bang Bang Control Flight Testing System Identification Elevator Deflection Probability Distribution Dynamic Programming algorithm Flight Path Angle robust algorithm Flight Envelope

来源：评论

学校读者我要写书评

暂无评论

robust Structure from Motion of Nonrigid Objects in the Presence of Outlying and Missing Data

Robust Structure from Motion of Nonrigid Objects in the Pres...

引用

10th International Conference on Computer and Robot Vision (CRV)

作者： Wang, Guanghui Zelek, John S. Wu, Q. M. Jonathan Univ Waterloo Dept Syst Design Engn 200 Univ Ave West Waterloo ON N2L 3G1 Canada Univ Windsor Dept Elect & Comp Engn Windsor ON N9B 3P4 Canada

ISBN: (纸本)9780769549835

The paper focuses on robust 3D structure from motion of nonrigid objects from uncalibrated image sequences. A new affine factorization algorithm is first proposed to avoid the difficulty in image alignment for imperfect data, followed by a robust factorization scheme to handle outlying and missing data. The novelty and main contributions of the paper are as follows: (i) as a new addition to previous nonrigid structure from motion, the proposed factorization algorithm can perfectly handle imperfect tracking data;(ii) it is demonstrated that the image reprojection residuals are in general proportional to the error magnitude of the tracked features. Thus, the outliers can be detected directly from the residuals, which are then used to estimate the uncertainties of the image measurement;and (iii) the robust factorization scheme is proved empirically to be more efficient and more accurate than other robust algorithms. The proposed approach is validated and evaluated by extensive experiments on synthetic data and real image sequences.

关键词： computer vision structure from motion nonrigid factorization robust algorithm

来源：评论

学校读者我要写书评

暂无评论

robust Clustered Federated Learning Against Malicious Agents 99

Robust Clustered Federated Learning Against Malicious Agents

引用

IEEE 99th Vehicular Technology Conference (VTC-Spring)

作者： Ngoh, Sisui Majumder, Abhishek Pal Duan, Lingjie Singapore Univ Technol & Design Engn Syst & Design Singapore Singapore Univ Reading Dept Math & Stat Berkshire England

ISBN: (纸本)9798350387414

Clustered Federated Learning (FL) is an extension of FL that organizes participating devices into clusters or groups, aiming to train heterogeneous models by grouping devices with diverse data distributions, thus fostering local collaboration within clusters for improved model performance. The increased model diversity introduces challenges stemming from the inherent heterogeneity in functions being modeled (e.g. for targeted advertising in platforms like Facebook), leading to a more natural prevalence of non-independent, non-identically distributed (non-IID) data in clustered FL environments. Moreover, another notable security challenge is that malicious agents can not only change their model updates to the aggregator but also misreport their cluster associations/identities in the clustered FL process. This paper introduces an algorithm called Coordinate-wise Median Clustered (CMC) to address the two challenges of heterogeneous model generation across agents and being robust against malicious agents. This is an algorithm that combines clustering and robust techniques, taking ideas from co-ordinate wise median attack-robust to adapt them to clustered FL. We prove that FedAvg per cluster does not converge under adversarial attacks while our CMC algorithm converges quickly to achieve high accuracy.

关键词： Clustered Federated Learning Heterogeneous models Adversarial agents robust algorithm

来源：评论

学校读者我要写书评

暂无评论

A robust Method for Estimating the Channel Data Rate in Seamless IEEE 802.11ax Standard Networks

A Robust Method for Estimating the Channel Data Rate in Seam...

引用

Conference on Systems of Signal Synchronization, Generating and Processing in Telecommunications (SYNCHROINFO)

作者： Spirina, E. A. Petrova, E. A. Kazan Natl Res Tech Univ Kazan Russia

ISBN: (纸本)9781665415491

In paper the robust method for estimating the channel data rate was developed for the collective dynamic routing method implementation in seamless IEEE 802.11ax standard networks. Collective dynamic routing method was analyzed with and without the use of a robust method in comparison with static routing by a seamless IEEE 802.11ax standard network segment example. The developed method makes it possible to significantly reduce the dimension of the valid routes set and, consequently, the computational complexity of the collective dynamic routing method implementation with a slight deterioration in its efficiency.

关键词： Wi-Fi networks IEEE 802.11ax channel data rate estimation robust algorithm collective dynamic routing method intra-system interference

来源：评论

学校读者我要写书评

暂无评论

DEEP MULTI-VIEW robust REPRESENTATION LEARNING

DEEP MULTI-VIEW ROBUST REPRESENTATION LEARNING

引用

IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Jiao, Zhenyu Xu, Chao Peking Univ Sch Elect Engn & Comp Sci Beijing 100871 Peoples R China

ISBN: (纸本)9781509041176

Multi-view representations are widely existed in practical applications, the quality of latent representation learned from multi-view observations often suffer from noise and outliers in original data. In this work, we propose an auto encoder based deep multi-view robust representation learning (DM-RRL) algorithm, which can learn a shared representation from multi-view observations and the algorithm is robust to noise and outliers by using Cauchy estimator as loss function. When the label of the original data is available, the algorithm can gain better representation by adding an auxiliary loss. We validate our methods on the CMU PIE dataset (noise applied) with face recognition task and UCF101 dataset with human motion recognition task, demonstrating that DMRRL is an effective algorithm for practical applications.

关键词： Multi-view learning Cauchy Estimators auto encoder robust algorithm

来源：评论

学校读者我要写书评

暂无评论

Statistical Query Lower Bounds for robust Estimation of High-Dimensional Gaussians and Gaussian Mixtures (Extended Abstract) 58

Statistical Query Lower Bounds for Robust Estimation of High...

引用

58th IEEE Annual Symposium on Foundations of Computer Science (FOCS)

作者： Diakonikolas, Ilias Kane, Daniel M. Stewart, Alistair Univ Southern Calif CS Los Angeles CA 90007 USA Univ Calif San Diego CSE & Math Los Angeles CA USA

ISBN: (纸本)9781538634646

We describe a general technique that yields the first Statistical Query lower bounds for a range of fundamental high-dimensional learning problems involving Gaussian distributions. Our main results are for the problems of (1) learning Gaussian mixture models (GMMs), and (2) robust (agnostic) learning of a single unknown Gaussian distribution. For each of these problems, we show a super-polynomial gap between the (information-theoretic) sample complexity and the computational complexity of any Statistical Query algorithm for the problem. Statistical Query (SQ) algorithms are a class of algorithms that are only allowed to query expectations of functions of the distribution rather than directly access samples. This class of algorithms is quite broad: a wide range of known algorithmic techniques in machine learning are known to be implementable using SQs. Moreover, for the unsupervised learning problems studied in this paper, all known algorithms with non-trivial performance guarantees are SQ or are easily implementable using SQs. Our SQ lower bound for Problem (1) is qualitatively matched by known learning algorithms for GMMs. At a conceptual level, this result implies that-as far as SQ algorithms are concerned-the computational complexity of learning GMMs is inherently exponential in the dimension of the latent space-even though there is no such information-theoretic barrier. Our lower bound for Problem (2) implies that the accuracy of the robust learning algorithm in [29] is essentially best possible among all polynomial-time SQ algorithms. On the positive side, we also give a new (SQ) learning algorithm for Problem (2) achieving the information-theoretically optimal accuracy, up to a constant factor, whose running time essentially matches our lower bound. Our algorithm relies on a filtering technique generalizing [29] that removes outliers based on higher-order tensors. Our SQ lower bounds are attained via a unified moment-matching technique that is useful in other

关键词： unsupervised learning statistical learning statistical queries robust algorithm

来源：评论

学校读者我要写书评

暂无评论

Performance Study of NVL Technique Based robust Uniform Concentric Circular Array Beamformer under Mismatch Condition

Performance Study of NVL Technique Based Robust Uniform Conc...

引用

IEEE-Region-10 Symposium (TENSYMP) - Technology for Impactful Sustainable Development

作者： Reza, Md Farhamdur Hossain, Md Selim Rashid, Md Mamunur Rajshahi Univ Engn & Technol RUET Dept Elect & Elect Engn Rajshahi 6204 Bangladesh

ISBN: (纸本)9781728173665

The performance of Uniform Concentric Circular Array (UCCA) by adopting robust technique is analyzed in this paper. The inter-element spacing and the interring spacing this UCCA structure is kept uniformly as half wavelength. UCCA is chosen because of its circular structure and it has the ability to scan the desired signal from 00 to 3600. If there is any mismatch between actual signal and steering directions, the performance of Minimum Variance Distortion-less Response (MVDR) will degrade will degrade. Different loading techniques can resolve the problem for mismatch and make the system robust enough to receive the anticipated signal in the presence of inequality between actual and steering direction. A New Variable Loading (NVL) based UCCA beamformer is proposed in this work and compared the performance with existing loading technique-based UCCA beamformers. It is observed that the proposed UCCA beamformer exhibits better interference attenuation capability and offers better robustness against mismatch compared to the existing beamformers. The performance of proposed NVL based beamformer is analyzed using MATLAB software.

关键词： Beamforming Smart antenna Diagonal Loading NVL technique robust algorithm

来源：评论

学校读者我要写书评

暂无评论

robust Beamforming and Power Control for Multiuser Cognitive Radio Network

Robust Beamforming and Power Control for Multiuser Cognitive...

引用

IEEE Global Telecommunications Conference (GLOBECOM 2010)

作者： Wang, Fanggang Wang, Wenbo Beijing Univ Posts & Telecommun Wireless Signal Proc & Network Lab Beijing 100876 Peoples R China

ISBN: (纸本)9781424456383

In multiuser cognitive radio (CR) network, we address the problem of joint transmit beamforming (BF) and power control (PC) for secondary users (SUs) when they are allowed to transmit simultaneously with primary users (PUs). The objective is to optimize the network sum rate under the interference constraints of PUs. Due to lack of cooperation among different nodes in the network, channel uncertainty is considered. In a worst case philosophy, a closed-form worst-case expression is derived, with which the uncertainty optimization problem is transformed into a certain one. Second-order cone programming approximation (SOCPA) method is proposed as a robust algorithm. Typical network models are approximated to second-order cone programming problems and solved by interior-point method. Finally the network sum rates for different PU and SU numbers are assessed for both certainty and uncertainty channel models by simulation.

关键词： Cognitive radio beamforming power control channel uncertainty robust algorithm second-order cone programming

来源：评论

学校读者我要写书评

暂无评论

Distributed and robust Support Vector Machine

引用

International Journal of Computational Geometry and Applications 2020年第3-4期30卷 213-233页

作者： Liu, Yangwei Ding, Hu Huang, Ziyun Xu, Jinhui Department of Computer Science and Engineering State University of New York at Buffalo Buffalo 14260-1660 NY United States School of Computer Science and Technology University of Science and Technology of China Hefei Anhui China Department of Computer Science and Software Engineering Penn State Erie Behrend College Erie 16563 PA United States

In this paper, we consider the distributed version of Support Vector Machine (SVM) under the coordinator model, where all input data (i.e., points in d space) of SVM are arbitrarily distributed among k nodes in some network with a coordinator which can communicate with all nodes. We investigate two variants of this problem, with and without outliers. For distributed SVM without outliers, we prove a lower bound on the communication complexity and give a distributed (1 - )-approximation algorithm to reach this lower bound, where is a user specified small constant. For distributed SVM with outliers, we present a (1 - )-approximation algorithm to explicitly remove the influence of outliers. Our algorithm is based on a deterministic distributed top t selection algorithm with communication complexity of O(klog(t)) in the coordinator model. © 2020 World Scientific Publishing Company.

关键词： communication complexity Distributed algorithm robust algorithm SVM

来源：评论

学校读者我要写书评

暂无评论

Improved algorithms for High-dimensional robust PCA 16

Improved Algorithms for High-dimensional Robust PCA

引用

16th IEEE International Conference on Ubiquitous Wireless Broadband (ICUWB)

作者： Lin, Xiaoyong Zhang, Zeqiu Wang, Jue Zhang, Zhaoyang Qiu, Tingting Mi, Zhengkun NUPT Nanjing 210003 Jiangsu Peoples R China Zhejiang Univ Hangzhou 310058 Zhejiang Peoples R China

ISBN: (纸本)9781509013173

Principal component analysis (PCA) is one of the most crucial dimensionality reduction methods and widely used in satellite image analysis, face recognition, social network feature extraction and other application scenarios. But it is fragile because of its quadratic error criterion when faced with outliers. There arc many robust PCAs to solve this problem, however, when extended to the high-dimensional set, in which the dimensionality of dataset is comparable to the number of observations, the quality of their output will suffer dramatically. So the high-dimensional robust PCA is needed eagerly. HR-PCA and DHR-PCA are exactly the algorithms designed for this regime. They are robust and fit for high-dimensional space. However, attention has to be paid to the low efficiency and loss of useful information respectively in these two algorithms. Two improved algorithms are proposed in this paper to address these issues. Firstly, a preprocessing mechanism is added before performing HR-PCA so as to reduce the burden of HR-PCA. Secondly, we take different ways of changing weights of observations according to their outlyingness instead of decreasing all weights in DHR-PCA. From the simulation results, the improved algorithms are robust enough and have stable performance.

关键词： high-dimensional data Principal component analysis feature extraction robust algorithm

来源：评论

学校读者我要写书评

暂无评论

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：

请选择收藏分类：

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

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：