检索结果-内蒙古大学图书馆

Reliability of projection algorithms in conditional estimation

JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 1999年第1期101卷 1-14页

作者： Garulli, A Kacewicz, BZ Vicino, A Zappa, G Univ Siena Dipartimento Ingn Informaz I-53100 Siena Italy Univ Min & Met Krakow Dept Appl Math Krakow Poland Univ Florence Dipartimento Sistemi & Informat Florence Italy

This paper studies the role of projection algorithms in conditional set membership estimation. These algorithms are known to be suboptimal in terms of the worst-case estimation error. A tight upper bound on the error of central projection estimators and interpolatory projection estimators is computed as a function of the conditional radius of information. Since the radius of information represents the minimum achievable error, the derived bound provides a measure of the reliability level of the suboptimal algorithms. The results are derived in a general deterministic setting, which allows the consideration of linearly parametrized approximations of a compact set of feasible problem elements.

关键词： set membership estimation linear models projection algorithms conditional estimation worst-case error

来源：评论

学校读者我要写书评

暂无评论

EVALUATION OF projection algorithms

引用

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 1981年第6期3卷 701-708页

作者： BISWAS, G JAIN, AK DUBES, RC Department of Computer Science Michigan State University East Lansing MI 48824

A number of linear and nonlinear mapping algorithms for the projection of patterns from a high-dimensional space to two dimensions are available. These two-dimensional representations allow quick visual observation of a data set. A combination of two popular mapping algorithms-Sammon"s mean-square error technique and the triangulation method-is proposed to overcome the limitations in the individual algorithms. Some factors which describe the goodness of a projection are described, and a comparison is made of six of these algorithms by running them on four data sets. The results obtained support the use of the proposed algorithm.

关键词： projection algorithms Signal processing algorithms Digital signal processing Fast Fourier transforms Speech processing Image processing Pattern recognition Data analysis Gold Signal processing Author Keywords two-dimensional projection Exploratory data analysis linear mapping minimum spanning tree nonlinear mapping pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Low Complexity and Robust Diffusion Affine projection algorithms for Distributed Estimation

引用

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2022年第3期69卷 1952-1956页

作者： Nautiyal, Mayank Bhattacharjee, Sankha Subhra George, Nithin, V Indian Inst Technol Gandhinagar Dept Elect Engn Gandhinagar 382355 India

Diffusion affine projection algorithms have the ability to de-correlate the input signal and have faster convergence but with the expense of increased computational complexity. Moreover, traditional diffusion affine projection algorithms consider the noise to be of Gaussian nature. However, practically this noise can be non-Gaussian which can significantly deteriorate the convergence of the algorithms. To mitigate this issue in this brief, we propose two robust affine projection algorithms based on the generalized maximum correntropy criterion (d-A-GMCC) and the logarithmic hyperbolic cosine cost function (d-A-lncosh). To reduce the computational expense of the proposed algorithms, we propose dichotomous coordinate descent based d-A-GMCC and d-A-lncosh algorithms. Extensive simulation study for different Gaussian and non-Gaussian noise environments shows the improved estimation ability of proposed algorithms.

关键词： projection algorithms Computational complexity Costs Cost function Computational modeling Kernel Estimation Distributed networks lncosh cost GMCC criterion low complexity DCD correntropy affine projection

来源：评论

学校读者我要写书评

暂无评论

OPTIMALITY OF CENTRAL AND projection algorithms FOR BOUNDED UNCERTAINTY

引用

SYSTEMS & CONTROL LETTERS 1986年第2期8卷 161-171页

作者： KACEWICZ, BZ MILANESE, M TEMPO, R VICINO, A POLITECN TORINO DIPARTIMENTO AUTOMAT & INFORMAT I-10129 TURIN ITALY CNR CTR ELABORAZ NUMERALE SEGNALI TURIN ITALY

This paper investigates optimality properties of central and projection algorithms for linear problems in the field of system identification in a context in which uncertainty is described in a deterministic rather than statistical way. Particular attention is devoted to least-squares algorithms when the measurement noise is assumed to be unknown but bounded in a Hilbert norm. A major contribution of this paper consists in proving that least-squares algorithms enjoy strong optimality properties. On the contrary, it is pointed out that these properties do not hold for other frequently used projection algorithms, such as least-absolute-values or minimax algorithms, corresponding to a description of the measurement error in h or l ∞ norm, respectively.

关键词： Linear problems System identification Deterministic uncertainty projection algorithms Least squares Local errors Strongly optimal algorithms

来源：评论

学校读者我要写书评

暂无评论

Tight error bounds for projection algorithms in conditional set membership estimation

引用

SYSTEMS & CONTROL LETTERS 1999年第5期37卷 293-300页

作者： Garulli, A Univ Siena Dipartimento Ingn Informaz I-53100 Siena Italy

In set membership estimation, conditional problems arise when the estimate must belong to a given set of assigned structure. Conditional projection algorithms provide estimates that are suboptimal in. terms of the worst-case estimation error. In order to precisely evaluate the suboptimality level of these estimators, tight upper bounds on the estimation errors must be computed as a function of the conditional radius of information, which represents the minimum achievable error. In this paper, tight bounds are derived for l(infinity) and l(1) estimation errors, in a general setting which allows to consider any compact set of feasible problem elements and linearly parameterized estimates. (C) 1999 Elsevier Science B.V. All rights reserved.

关键词： set membership estimation identification bounded errors projection algorithms

来源：评论

学校读者我要写书评

暂无评论

On sequential and parallel projection algorithms for feasibility and optimization

On sequential and parallel projection algorithms for feasibi...

引用

Conference on Visualization and Optimization Techniques

作者： Censor, Y Univ Haifa Dept Math IL-31905 Haifa Israel

ISBN: (纸本)081944281X

The convex feasibility problem of finding a point in the intersection of finitely many nonempty closed convex sets in the Euclidean space has many applications in various fields of science and technology, particularly in problems of image reconstruction from projections, in solving the fully discretized inevrse problem in radiation therapy treatment planning, and in other image processing problems. Solving systems of linear equalities and/or inequalities is one of them. Many of the existing algorithms use projections onto the sets and may: (i) employ orthogonal-, entropy-, or other Bregman-projections, (ii) be structurally sequential, parallel, block-iterative, or of the string-averaging type, (iii) asymptotically converge when the underlying system is, or is not, consistent, (iv) solve the convex feasibility problem or find the projection of a given point onto the intersection of the convex sets, (v) have good initial behavior patterns when some of their parameters are appropriately chosen.

关键词： projection algorithms Block-iterative Bregman projections convex feasibility string-averaging

来源：评论

学校读者我要写书评

暂无评论

IMPROVED projection algorithms FOR LONG-TERM AND HIGH-RESOLUTION SATELLITE DATASETS

IMPROVED PROJECTION ALGORITHMS FOR LONG-TERM AND HIGH-RESOLU...

引用

IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Garcia-Espriu, A. Gonzalez-Haro, C. Gonzalez-Gambau, V Olmedo, E. Turiel, A. CSIC Barcelona Expert Ctr BEC Barcelona Spain CSIC Inst Marine Sci ICM Barcelona Spain

ISBN: (纸本)9798350360332;9798350360325

Satellite mission datasets increase in size as their life span grows and the resolutions of the instruments increase. Accurately projecting antenna-based satellite measurements on a geographical grid while maintaining reasonable computational time and costs can be challenging. It is thus necessary to include big data algorithms and dedicated management techniques in the processing of such datasets. In this regard, the optimization of the number of interpolations and projections is one of the key aspects, as the native errors of the measurements propagate at each processing step. Besides each interpolation and projection implies a non-negligible increase in total computational time. This work is based on the Sea Surface Salinity (SSS) processor of the Soil Moisture and Ocean Salinity (SMOS) mission, but it could be easily extended to any other satellite mission where individual values for each measurement are retrieved. We propose a redefinition of the complete processor chain so it can work with the measurements within the instrument coordinate system. This allows us to avoid projectionrelated errors during the generation of the final product. Additionally, we introduce a novel algorithm to project those measurements taking into account the actual spatial extent of the acquisitions instead of taking them as points, so measures are averaged weighted by the area they cover on the Earth-based grid. This method is optimized to transform 2D areas into discrete measurements, increasing its computational efficiency and favoring parallelization. Our algorithm has demonstrated its potential when incorporated into the SMOS SSS processor at the Barcelona Expert Center (BEC), allowing us to keep a final resolution very close to the one attained at the antenna coordinate system.

关键词： Sea Surface Salinity Remote Sensing SMOS Big Data projection algorithms

来源：评论

学校读者我要写书评

暂无评论

projection algorithms for l q -Norm Bounded-Noise Data

引用

IFAC Proceedings Volumes 1997年第11期30卷 1345-1349页

作者： Karel Keesman Systems and Control Group Wageningen Agricultural University Bomenweg 4 6703 HD Wageningen The Netherlands

In this paper a classification, according to the leading principle (a) intersection, (b) encapsulation, and (c) projection, of outer-bounding algorithms for the identification from data with bounded uncertainty is provided. In particular, the paper focuses on the properties of l p -projection algorithms for the approximation of the exact solution set and their possibilities for application in a set-membership context with l q -norm bounded uncertainty.

关键词： Set-membership identification projection algorithms bounded noise

来源：评论

学校读者我要写书评

暂无评论

projection algorithms for two-dimensional adaptive filtering applications

Projection algorithms for two-dimensional adaptive filtering...

引用

Asilomar Conference on Signals, Systems & Computers

作者： R.A. Soni W.K. Jenkins Coordinated Science Laboratory Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign Urbana-Champaign IL USA University of Illinois at Urbana-Champaign Urbana IL US

In this paper we present a family of "new" two-dimensional adaptive filtering algorithms for image processing applications. These algorithms are multidimensional versions of the families of data-reusing and projection algorithms. These two classes of algorithms allow the adaptive filtering system designer to choose performance and computational complexity by changing parameters without actually changing algorithm structure. By changing parameters, the desired convergence rate can be achieved at the expense of additional computational complexity. Experiments show that significant improvement may be obtained by marginal increases in computational complexity over the traditional normalized LMS algorithm.

关键词： projection algorithms Adaptive filters Filtering algorithms Convergence Least squares approximation Application software Computational complexity Tin Algorithm design and analysis Autocorrelation

来源：评论

学校读者我要写书评

暂无评论

Fast alternated inertial projection algorithms for pseudo-monotone variational inequalities

引用

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 2022年 415卷

作者： Shehu, Yekini Dong, Qiao-Li Liu, Lu-Lu Zhejiang Normal Univ Coll Math & Comp Sci Jinhua 321004 Zhejiang Peoples R China Civil Aviat Univ China Coll Sci Tianjin 300300 Peoples R China

In this paper, we propose an alternated inertial subgradient extragradient algorithm for variational inequalities with self-adaptive step-sizes and obtain weak and linear convergence results. We also obtain linear convergence results using an alternated inertial projected gradient algorithm for which knowledge of the modulus of strong pseudomonotonicity and Lipschitz constant of the cost function are not needed. We compare numerically our algorithms with other projection-type algorithms in the literature. (C) 2022 Elsevier B.V. All rights reserved.

关键词： projection algorithms Variational inequality Pseudo-monotone operator Weak convergence Linear rate Hilbert spaces

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：