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Data compression by removing redundant points

version 1.1.0.0 (2.13 KB) by Yuriy Skalko
The function removes redundant data points from the 2D data.

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Updated 27 Nov 2012

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The function removes redundant data points within EPS tolerance interval using GE Historian Compression algorithm (similar to Swinging Door algorithm) described here: http://www.evsystems.net/files/GE_Historian_Compression_Overview.ppt

Cite As

Yuriy Skalko (2020). Data compression by removing redundant points (https://www.mathworks.com/matlabcentral/fileexchange/39081-data-compression-by-removing-redundant-points), MATLAB Central File Exchange. Retrieved .

Comments and Ratings (6)

Imran

Ronan CIMADURE

Yuriy Skalko

Thank you for feedback, Per.

I've tried your sample inputs and cannot see any problem with compressed outputs. The last point is always included into output points. Could you send the output that you expected?

I have no much experience with Swinging Door algorithm, but it has approximately the same compression level as GE Historian. I don't have data, used on this slide and will be unable to explain achieved compression ratio in this example.

per isakson

Thank you for this code and the reference.

I think, there is a minor problem with logic of the while-loop. The second last point cannot be included in the compressed sequence, (xc,yc).

This set of input data illustrates the problem.

y = [1.0,1.1,1.2,1.1,0.9,0.7,0.3,2.1,2.0,2.0,1.7];
x = ( 1 : length( x ) );
eps = 0.1;

The second last slide in the ppt-file shows a comparison between two compression methods. I'm not sure what "xH" refers to, but it ought to be "GE Historian". If that is the case, I cannot understand the large difference in compression ratio between the two.

Yuriy Skalko

Hello, ses. What you mean by "XCV"?

ses

XCV

MATLAB Release Compatibility
Created with R2010a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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