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Eigen Function of the Laplacian

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Eigen Function of the Laplacian

by Ambarish Jash

 

01 Nov 2010 (Updated 03 Nov 2010)

The main file Diffusion_Family.m gives a low dimensional embedding in 3 different ways.

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Description

The different low dimensional embeddings are an orthonormal coordinate system generated from a
1. Diffusion process defined on the data
2 . Normalized Laplace Beltrami operator
3. Normalized Focker Plank operator

This is a nonlinear dimension reduction technique using the concepts of manifold learning. The image is color coded. (2 data sets which are 2 dimensional each are being clustered using this algorithm using the first three non trivial eigen function of the normalized Focker Plank operator)

MATLAB release MATLAB 7.10 (2010a)
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Updates
03 Nov 2010

There was a minor correction in line 101.

03 Nov 2010

Change in description to accurately depict the image

Tag Activity for this File
Tag Applied By Date/Time
signal processing Ambarish Jash 02 Nov 2010 10:59:23
data exploration Ambarish Jash 02 Nov 2010 10:59:23
modeling Ambarish Jash 02 Nov 2010 10:59:23
dimension reduction Ambarish Jash 02 Nov 2010 10:59:23
manifold learning Ambarish Jash 02 Nov 2010 10:59:23
nonlinear Ambarish Jash 02 Nov 2010 10:59:23
diffusion maps laplacian eigenmaps Ambarish Jash 03 Nov 2010 13:10:43

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