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A DIMENSION REDUCTION-BASED METHOD FOR CLASSIFICATION OF HYPERSPECTRAL AND LIDAR DATA
Hyperspectral Image Lidar Data Dimension Reduction SVM Classification Fusion
2016/1/15
The existence of various natural objects such as grass, trees, and rivers along with artificial manmade features such as buildings and roads, make it difficult to classify ground objects. Consequently...
A Unified Near-Optimal Estimator For Dimension Reduction in lα (0 < α ≤ 2) Using Stable Random Projections
Near-Optimal Estimator Dimension Reduction Stable Random Projections
2015/8/21
Many tasks (e.g., clustering) in machine learning only require the lα distances instead of the original data. For dimension reductions in the lα norm (0 < α ≤ 2), the method of stable random projectio...
Nonlinear Estimators and Tail Bounds for Dimension Reduction in l1 Using Cauchy Random Projections
dimension reduction l1 norm Johnson-Lindenstrauss (JL) lemma Cauchy random projections
2015/8/21
For1 dimension reduction in the l1 norm, the method of Cauchy random projections multiplies the original data matrix A ∈ Rn×D with a random matrix R ∈ RD×k (k D) whose entries are i.i.d. samples of ...
Research on dimension reduction method for hyperspectral remote sensing image based on global mixture coordination factor analysis
Dimension reduction Coordination factor analysis Hyperspectral remote sensing Feature construction Manifold learning
2015/7/27
Over the past thirty years, the hyperspectral remote sensing technology is attracted more and more attentions by the researchers. The dimension reduction technology for hyperspectral remote sensing im...
FUSION OF HYPERSPECTRAL AND LIDAR DATA BASED ON DIMENSION REDUCTION AND MAXIMUM LIKELIHOOD
Lidar, Hyper-spectral Fusion Classification
2015/5/6
Limitations and deficiencies of different remote sensing sensors in extraction of different objects caused fusion of data from different sensors to become more widespread for improving classificatio...
Topics in Multivariate Time Series Analysis: Statistical Control, Dimension Reduction Visualization and Thir Business Applications
Topics in Multivariate Time Series Analysis Statistical Control Dimension Reduction Visualization Their Business Applications
2014/10/28
Most business processes are, by nature, multivariate and autocorrelated. Highdimensionality is rooted in processes where more than one variable is considered simultaneously to provide a more comprehen...
Surrogate-based modeling and dimension reduction techniques for multi-scale mechanics problems
Multi-scale mechanics Cryogenic cavitating flow Surrogate-based modeling Active flow control Engineering system
2012/2/28
Successful modeling and/or design of engineering systems often requires one to address the impact of multiple “design variables” on the prescribed outcome. There are often multiple, competing objectiv...
Deciding the dimension of effective dimension reduction space for functional and high-dimensional data
effective dimension reduction space high-dimensional data
2010/11/18
In this paper, we consider regression models with a Hilbert-space-valued predictor and a scalar response, where the response depends on the predictor only through a finite number of projections. The ...
Deformation-based nonlinear dimension reduction: applications to nuclear morphometry
nonlinear dimension dimension reduction nuclear shape analysis
2009/12/23
Deformation-based nonlinear dimension reduction: applications to nuclear morphometry.
Selection of variables and dimension reduction in high-dimensional non-parametric regression
dimension reduction high dimension LASSO
2009/9/16
We consider a $l_1$-penalization procedure in the non-parametric Gaussian regression model. In many concrete examples, the dimension $d$ of the input variable $X$ is very large (sometimes depending on...
Theoretical properties of Cook's PFC dimension reduction algorithm for linear regression
Principal Components Principal Fitted Components random matrix theory regression
2009/9/16
We analyse the properties of the Principal Fitted Components (PFC) algorithm proposed by Cook. We derive theoretical properties of the resulting estimators, including sufficient conditions under which...
Dimension Reduction of Solid Models by Mid-Surface Generation
Dimensional reduction Mid-surface Geometry replacement
2009/8/19
Recently, feature-based solid modeling systems have been widely used in product design. However, for engineering analysis of a product model, an abstracted CAD model composed of mid-surfaces is desira...
Dimension Reduction Method in Thermodynamics of Multireaction Systems* Residual Properties, Property Changes of Mixing and Excess Properties Relations
thermodynamics phase equilibrium multireaction
2009/4/22
Based on the fundamental thermodynamic principle the relationships of the residual properties, the property changes of mixing and the excess properties between the hypothetical solution of unreacted i...
Dimension Reduction Method in Thermodynamics of Multireaction Systems (I) Mole Numbers, Thermodynamic Properties and Partial Molar Properties Relations
thermodynamics phase equilibrium multireactio
2009/4/22
Dimension Reduction Method in Thermodynamics of Multireaction Systems (I) Mole Numbers, Thermodynamic Properties and Partial Molar Properties Relations.
Dimension reduction in representation of the data
Data representation data analysis data mining
2010/3/18
Suppose the data consist of a set S of points xj , 1 ≤ j ≤ J, distributed in a
bounded domain D RN, where N is a large number. An algorithm is given
for finding the sets Lk of dimension k N, k = 1, ...