https://github.com/lemire/lbimproved
Dynamic Time Warping (DTW) library implementing lower bounds (LB_Keogh, LB_Improved...)
https://github.com/lemire/lbimproved
c-plus-plus dtw lower-bounds warping
Last synced: over 1 year ago
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Dynamic Time Warping (DTW) library implementing lower bounds (LB_Keogh, LB_Improved...)
- Host: GitHub
- URL: https://github.com/lemire/lbimproved
- Owner: lemire
- License: apache-2.0
- Created: 2015-03-12T23:05:51.000Z (over 11 years ago)
- Default Branch: master
- Last Pushed: 2020-01-30T13:49:02.000Z (over 6 years ago)
- Last Synced: 2025-02-27T13:23:34.864Z (over 1 year ago)
- Topics: c-plus-plus, dtw, lower-bounds, warping
- Language: C++
- Homepage:
- Size: 35.2 KB
- Stars: 112
- Watchers: 11
- Forks: 28
- Open Issues: 2
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Metadata Files:
- Readme: README.md
- License: LICENSE.txt
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README
# LBImproved C++ Library
[](https://travis-ci.org/lemire/lbimproved)
This library comes in the form of one short C++ header file. The documentation
is in the C++ comments and in this file.
# Key feature
1) Fast Dynamic Time Warping nearest neighbor retrieval.
2) Implementations of LB Koegh and LB Improved
3) Companion to the following paper :
Daniel Lemire, Faster Retrieval with a Two-Pass Dynamic-Time-Warping Lower Bound, Pattern Recognition 42 (9), pages 2169-2180, 2009.
http://arxiv.org/abs/0811.3301
Comments about this paper by Keogh's team:
To our knowledge, there is only one paper that
offers a plausible speedup based on a tighter
lower bound—Lemire (2009) suggests a mean speedup
of about 1.4 based on a tighter bound.
These results are reproducible, and testing on
more general data sets we obtained similar
results (...) (Wang et al. 2013)
# BUILD
type "make"
make
./unittesting
./benchmark
./example
# Simple code example
See ``example.cpp``.
# Other libraries
* [dtwclust](https://github.com/asardaes/dtwclust) is an R Package for Time Series Clustering Along with Optimizations for DTW