From 3c9315bcc9674a27c41aa281e168cf0207ccf4be Mon Sep 17 00:00:00 2001
From: Alexander Nikitin <1243786+AlexanderVNikitin@users.noreply.github.com>
Date: Sat, 30 Mar 2024 19:54:35 +0200
Subject: [PATCH] add dtw to readme

---
 README.md | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index 502bb6f..9138160 100644
--- a/README.md
+++ b/README.md
@@ -125,9 +125,10 @@ TSGM provides a number of time series augmentations.
 | ------------- | ------------- | ------------- |
 | Gaussian Noise / Jittering  | `tsgm.augmentations.GaussianNoise` | -  |        
 | Slice-And-Shuffle  | `tsgm.augmentations.SliceAndShuffle` | - |
-| Shuffle features  | `tsgm.augmentations.Shuffle` | - |
-| Magnitude warping  | `tsgm.augmentations.MagnitudeWarping` | [Data Augmentation of Wearable Sensor Data for Parkinson’s Disease Monitoring using Convolutional Neural Networks](https://dl.acm.org/doi/pdf/10.1145/3136755.3136817) |
-| Window warping  | `tsgm.augmentations.WindowWarping` | [Data Augmentation for Time Series Classification using Convolutional Neural Networks](https://shs.hal.science/halshs-01357973/document) |
+| Shuffle Features  | `tsgm.augmentations.Shuffle` | - |
+| Magnitude Warping  | `tsgm.augmentations.MagnitudeWarping` | [Data Augmentation of Wearable Sensor Data for Parkinson’s Disease Monitoring using Convolutional Neural Networks](https://dl.acm.org/doi/pdf/10.1145/3136755.3136817) |
+| Window Warping  | `tsgm.augmentations.WindowWarping` | [Data Augmentation for Time Series Classification using Convolutional Neural Networks](https://shs.hal.science/halshs-01357973/document) |
+| DTW Barycentric Averaging  | `tsgm.augmentations.DTWBarycentricAveraging` | [A global averaging method for dynamic time warping, with applications to clustering.](https://www.sciencedirect.com/science/article/pii/S003132031000453X) |
 
 
 ## Contributing