检索结果-内蒙古大学图书馆

multiplicative algorithm for computing D-optimum designs for pVT measurements

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS 2012年第1期111卷 20-27页

作者： Martin-Martin, Raul Rodriguez-Aragon, Licesio J. Torsney, Ben Sch Comp Sci E-13071 Ciudad Real Spain Sch Architecture E-45071 Toledo Spain Univ Glasgow Sch Math & Stat Glasgow G12 8QW Lanark Scotland Univ Castilla La Mancha Dept Matemat Inst Matemat Aplicada Ciencia & Ingn E-13071 Ciudad Real Spain

Multifactor models are present in industry and in biological experiments: therefore optimum designs are a valuable tool for experimenters, leading to estimators of the parameters with minimum variance. A generalization of the multiplicative algorithm to find locally D-optimum designs for multifactor models as Tait-like equations is here proposed. The method consists of transforming a conceived set of design points over a finite interval into proportions of the design interval defined by the sub-intervals between successive points. Examples for different modifications of the Tait equation are here presented: a three parameter model under isothermal conditions with pressure as the independent variable and two different modifications of an eight parameter model (Rackett equation) with pressure and temperature as design variables. Optimum design for the first example is equally supported at three points while the two-factor modifications of the Tait equation show designs with more support points than unknown parameters and different weights for each point Efficiencies of real experimental designs are computed and suitable more efficient experimental designs, satisfying experimental demands are also proposed. (C) 2011 Elsevier B.V. All rights reserved.

关键词： D-optimum design Tait equation multiplicative algorithm 2008 MSC: 62K05

来源：评论

学校读者我要写书评

暂无评论

multiplicative algorithm for discriminating between Arrhenius and non-Arrhenius behaviour

引用

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS 2014年 139卷 146-155页

作者： Martin-Martin, Raul Dorta-Guerra, Roberto Torsney, Ben Sch Architecture E-45071 Toledo Spain Dept Math Stat & Operat Res E-38271 San Cristobal la Laguna Spain Univ Glasgow Sch Math & Stat Glasgow G12 8QW Lanark Scotland

The Arrhenius equation k(A) = Ae(-E/Rt) has found numerous applications throughout chemical kinetics for diverse rate processes. This equation involves the assumption that the pre-exponential factor, A, does not vary with temperature. For simple reactions, deviations from this equation are usually quite small, and in only a few instances are they at all readily detectable. However kinetic measurements over wide ranges of temperature show up the inadequacy of the Arrhenius expression (Smith, 2008 [1]). The temperature dependence of the linear parameter is widely used as an alternative model. Consequently, a correct selection of the model and a correct estimation of the parameters are crucial tasks. The focus of this paper is the construction of a new procedure based on the multiplicative algorithm in order to determining optimal experimental conditions for discriminating between two rival models. Even for moderate examples the calculation of T-optimal designs is not straightforward. There are no known specific iterative numerical techniques for constructing T-optimum designs;there is just the classical adaptation of the Wynn-Fedorov scheme (Atkinson and Fedorov, 1975;Fedorov and Hackl, 1997), which is far from being satisfactory to solve these computational problems. The results are illustrated by numerical examples for different deviations of the Arrhenius equation. On the other hand we demonstrate in several examples that the new algorithm is more efficient than those existing in the literature. (C) 2014 Elsevier B.V. All rights reserved.

关键词： T-optimum design Arrhenius equation Modified Arrhenius equation multiplicative algorithm

来源：评论

学校读者我要写书评

暂无评论

A multiplicative algorithm for Convolutive Non-Negative Matrix Factorization Based on Squared Euclidean Distance

引用

IEEE TRANSACTIONS ON SIGNAL PROCESSING 2009年第7期57卷 2858-2864页

作者： Wang, Wenwu Cichocki, Andrzej Chambers, Jonathon A. Univ Surrey Dept Elect Engn Ctr Vis Speech & Signal Proc Guildford GU2 7XH Surrey England RIKEN Brain Sci Inst Lab Adv Brain Signal Proc Wako Saitama 3510198 Japan Univ Loughborough Adv Signal Proc Grp Dept Elect & Elect Engn Loughborough LE11 3TU Leics England

Using the convolutive nonnegative matrix factorization (NMF) model due to Smaragdis, we develop a novel algorithm for matrix decomposition based on the squared Euclidean distance criterion. The algorithm features new formally derived learning rules and an efficient update for the reconstructed nonnegative matrix. Performance comparisons in terms of computational load and audio onset detection accuracy indicate the advantage of the Euclidean distance criterion over the Kullback-Leibler divergence criterion.

关键词： Audio object separation convolutive nonnegative matrix factorization multiplicative algorithm squared Euclidean distance

来源：评论

学校读者我要写书评

暂无评论

multiplicative algorithms for computing optimum designs

引用

JOURNAL OF STATISTICAL PLANNING AND INFERENCE 2009年第12期139卷 3947-3961页

作者： Torsney, B. Martin-Martin, R. Univ Castilla La Mancha Inst Appl Math Sci & Engn Dept Math Sch Comp Sci E-13071 Ciudad Real Spain Univ Glasgow Dept Stat Glasgow G12 8QW Lanark Scotland

We Study a new approach to determine optimal designs, exact or approximate, both for the uncorrelated case and when the responses may be correlated. A simple version of this method is based on transforming design points on a finite interval to proportions of the interval. Methods for determining optimal design weights can therefore be used to determine optimal values of these proportions. We explore the potential of this method in a range of examples encompassing linear and non-linear models, some assuming a correlation structure and some with more than one design variable. (C) 2009 Elsevier EIN. All rights reserved.

关键词： Exact design Approximate design multiplicative algorithm Covariance function

来源：评论

学校读者我要写书评

暂无评论

multiplicative algorithms for Constrained Non-negative Matrix Factorization

Multiplicative Algorithms for Constrained Non-negative Matri...

引用

12th IEEE International Conference on Data Mining (ICDM)

作者： Peng, Chengbin Wong, Ka-Chun Rockwood, Alyn Zhang, Xiangliang Jiang, Jinling Keyes, David King Abdullah Univ Sci & Technol Comp Elect & Math Sci & Engn Thuwal Saudi Arabia Univ Toronto Dept Comp Sci Toronto ON Canada Aalborg Univ Dept Comp Sci Aalborg Denmark

ISBN: (纸本)9781467346498;9780769549057

Non-negative matrix factorization (NMF) provides the advantage of parts-based data representation through additive only combinations. It has been widely adopted in areas like item recommending, text mining, data clustering, speech denoising, etc. In this paper, we provide an algorithm that allows the factorization to have linear or approximatly linear constraints with respect to each factor. We prove that if the constraint function is linear, algorithms within our multiplicative framework will converge. This theory supports a large variety of equality and inequality constraints, and can facilitate application of NMF to a much larger domain. Taking the recommender system as an example, we demonstrate how a specialized weighted and constrained NMF algorithm can be developed to fit exactly for the problem, and the tests justify that our constraints improve the performance for both weighted and unweighted NMF algorithms under several different metrics. In particular, on the Movielens data with 94% of items, the Constrained NMF improves recall rate 3% compared to SVD50 and 45% compared to SVD150, which were reported as the best two in the top-N metric.

关键词： Non-negative Matrix Factorization Linear Constraints multiplicative algorithm

来源：评论

学校读者我要写书评

暂无评论

Finding optimal design in nonlinear mixed effect models using multiplicative algorithms

引用

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2021年 207卷 106126-106126页

作者： Seurat, Jeremy Tang, Yuxin Mentre, France Nguyen, Thu Thuy Univ Paris INSERM IAME F-75006 Paris France

Background and objectives: To optimize designs for longitudinal studies analyzed by nonlinear mixed effect models (NLMEMs), the Fisher information matrix (FIM) can be used. In this work, we focused on the multiplicative algorithms, previously applied in standard individual regression, to find optimal designs for ***: We extended multiplicative algorithms to mixed models and implemented the algorithm both in R and in C. Then, we applied the algorithm to find D-optimal designs in two longitudinal data examples, one with continuous and one with binary ***: For these examples, we quantified the improved speed when C is used instead of R. Design optimization using the multiplicative algorithm led to designs with D-efficiency gains between 13% and 25% compared to non-optimized ***: We found that the multiplicative algorithm can be used efficiently to design longitudinal studies.

关键词： Nonlinear mixed effect model Fisher information matrix multiplicative algorithm Optimal design D-optimality Longitudinal studies

来源：评论

学校读者我要写书评

暂无评论

multiplicative methods for computing D-optimal stratified designs of experiments

引用

JOURNAL OF STATISTICAL PLANNING AND INFERENCE 2014年 146卷 82-94页

作者： Harman, Radoslav Comenius Univ Dept Appl Math & Stat Fac Math Phys & Informat Bratislava 84248 Slovakia

Consider a linear regression experiment with uncorrelated real-valued observations and a finite design space. An approximate experimental design is stratified if it allocates given proportions of trials to selected non-overlapping partitions of the design space. To calculate an approximate D-optimal stratified design, we propose two multiplicative methods: a re-normalisation heuristic and a barycentric algorithm, both of which are very simple to implement. The re-normalisation heuristic is generally more rapid, but for the barycentric algorithm, we can prove monotonic convergence to the optimum. We also develop rules for the removal of design points that cannot support any D-optimal stratified design, which significantly improves the speed of both proposed multiplicative methods. (C) 2013 Elsevier B.V. All rights reserved.

关键词： D-optimal design Stratified design Marginal constraints multiplicative algorithm Barycentric algorithm

来源：评论

学校读者我要写书评

暂无评论

Strict monotonicity and convergence rate of Titterington's algorithm for computing D-optimal designs

引用

COMPUTATIONAL STATISTICS & DATA ANALYSIS 2010年第6期54卷 1419-1425页

作者： Yu, Yaming Univ Calif Irvine Dept Stat Irvine CA 92697 USA

We study a class of multiplicative algorithms introduced by Silvey et al. (1978) for computing D-optimal designs. Strict monotonicity is established for a variant considered by Titterington (1978). A formula for the rate of convergence is also derived. This is used to explain why modifications considered by Titterington ( 1978) and Dette et al. (2008) usually converge faster. (C) 2010 Elsevier By. All rights reserved.

关键词： D-optimality Experimental design multiplicative algorithm

来源：评论

学校读者我要写书评

暂无评论

Combined algorithm to compute D-optimal designs

引用

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 2015年 278卷 248-257页

作者： Martin Martin, Raul Camacha Gutierrez, Irene Garcia Univ Castilla La Mancha Dept Math Toledo Spain

algorithmic techniques for computing optimal designs continue being a need in the optimal experimental design field. The increasing interest in finding the optimal experimental conditions makes that new methods are demanded for more complex frameworks showing more realistic situations. Numerical techniques are often the unique viable option for computing these designs since to tackle analytically the problem results impracticable in most of cases. Wynn-Fedorov algorithm, multiplicative algorithm and their modifications are the more frequently used methods in the literature for computing D-optimal designs. However, they are not always suitable and efficient to compute optimal designs since their procedures are very limited by the computational requirements. A new algorithm to obtain D-optimal designs is proposed in this paper. It is based on combining suitable strategies followed by the traditional algorithms. A proof of the convergence is provided and several numerical examples are presented to illustrate its improved results. (C) 2014 Elsevier B.V. All rights reserved.

关键词： D-optimum design multiplicative algorithm Wynn-Fedorov algorithm Combined algorithm

来源：评论

学校读者我要写书评

暂无评论

Nonnegative matrix factorization-based hyperspectral and panchromatic image fusion

引用

NEURAL COMPUTING & APPLICATIONS 2013年第3-4期23卷 895-905页

作者： Zhang, Zhou Shi, Zhenwei Beihang Univ Image Proc Ctr Sch Astronaut Beijing 100191 Peoples R China Beihang Univ Beijing Key Lab Digital Media Beijing 100191 Peoples R China Beihang Univ State Key Lab Virtual Real Technol & Syst Beijing 100191 Peoples R China

The fusion of hyperspectral image and panchromatic image is an effective process to obtain an image with both high spatial and spectral resolutions. However, the spectral property stored in the original hyperspectral image is often distorted when using the class of traditional fusion techniques. Therefore, in this paper, we show how explicitly incorporating the notion of "spectra preservation" to improve the spectral resolution of the fused image. First, a new fusion model, spectral preservation based on nonnegative matrix factorization (SPNMF), is developed. Additionally, a multiplicative algorithm aiming at get the numerical solution of the proposed model is presented. Finally, experiments using synthetic and real data demonstrate the SPNMF is a superior fusion technique for it could improve the spatial resolutions of hyperspectral images with their spectral properties reliably preserved.

关键词： Hyperspectral image fusion Spectra preservation Nonnegative matrix factorization (NMF) multiplicative 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：