نتایج جستجو برای: lle

تعداد نتایج: 1147  

2010
Ming-Jer Lee Yu-Ching Kuo Pei-Jung Lien

The liquid-liquid equilibrium (LLE) phase boundaries were determined experimentally for the ternary systems containing refined sunflower oil, methanol, and one of ten potential cosolvents at 308.2 K under atmospheric pressure by using cloud point method. n-Butylamine was found to be one of the best cosolvents, which could substantially enhance the miscibility between the oil and methanol. The L...

2011
Xianlin Zou Qingsheng Zhu Yifu Jin J. Tenenbaum V De Silva Tony Lin Hongbin Zha Sang Uk Lee

Locally Linear Embedding (LLE) algorithm is the first classic nonlinear manifold learning algorithm based on the local structure information about the data set, which aims at finding the low-dimension intrinsic structure lie in high dimensional data space for the purpose of dimensionality reduction. One deficiency appeared in this algorithm is that it requires users to give a free parameter k w...

Journal: :Image Vision Comput. 2009
Nathan Mekuz Christian Bauckhage John K. Tsotsos

Subspace manifold learning represents a popular class of techniques in statistical image analysis and object recognition. Recent research in the field has focused on nonlinear representations; locally linear embedding (LLE) is one such technique that has recently gained popularity. We present and apply a generalization of LLE that introduces sample weights. We demonstrate the application of the...

2012
WANG QI

In this paper, the main application image processing, manifold learning and the method of Gaussian mixture model for dimensionality reduction and cluster analysis, the image color information are all studied. First, the color data access algorithm is introduced, secondly, the manifold learning in the local linear embedding (LLE) algorithm is used in color analysis; then the results of an evalua...

Journal: :Comput. Sci. Inf. Syst. 2009
Zuojin Li Weiren Shi Xin Shi Zhi Zhong

The Locally Linear Embedding (LLE) algorithm is an unsupervised nonlinear dimensionality-reduction method, which reports a low recognition rate in classification because it gives no consideration to the label information of sample distribution. In this paper, a classification method of supervised LLE (SLLE) based on Linear Discriminant Analysis (LDA) is proposed. First, samples are classified a...

2017
Tieqiang Liang Lijuan Wang

A new pH-sensing film was developed by using tamarind seed polysaccharide (TSP) and natural dye extracted from litmus lichen (LLE). The addition of LLE from 0 to 2.5% decreased the tensile strength and elongation at break from 30.20 to 29.97 MPa and 69.73% to 60.13%, respectively, but increased the water vapor permeability from 0.399 × 10−9 to 0.434 × 10−9 g·s−1·m−1·Pa−1. The UV–Vis spectra of ...

2014
A. Luca J.-M. Vesin A. Vlad

The present study investigates the potential of the Largest Lyapunov Exponent (LLE) for the quantification of AF complexity as a marker of antitachycardia pacing (ATP) effectiveness in a biophysical model of the human atria. From ongoing simulated atrial fibrillation, 20 transmembrane potential maps were used as initial conditions for a rapid pacing from the septum area (at pacing cycle length ...

2000
Lawrence K. Saul Sam T. Roweis

Many problems in information processing involve some form of dimensionality reduction. Here we describe locally linear embedding (LLE), an unsupervised learning algorithm that computes low dimensional, neighborhood preserving embeddings of high dimensional data. LLE attempts to discover nonlinear structure in high dimensional data by exploiting the local symmetries of linear reconstructions. No...

2017
C. M. Krauland P. Gourdain J. R. Davies

LLE Review, Volume 152 209 Under the facility governance plan implemented in FY08 to formalize the scheduling of the Omega Laser Facility as a National Nuclear Security Administration (NNSA) User Facility, Omega Facility shots are allocated by campaign. The majority (68.1%) of the FY17 target shots were allocated to the Inertial Confinement Fusion (ICF) Campaign conducted by integrated teams fr...

2013
J. Shalini R. Jayasree K. Vaishnavi

Clustering is the task of grouping a set of objects in such a way that objects in the same group (called cluster) are more similar (in some sense or another) to each other than to those in other groups (clusters). The dimension can be reduced by using some techniques of dimension reduction. Recently new non linear methods introduced for reducing the dimensionality of such data called Locally Li...

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