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Dynamic Time Warping

version 1.0 (1.47 KB) by

Dynamic time warping program. Calculates the similarity between 2 vectors.

4.08333
36 Ratings

35 Downloads

Updated

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If you pass in 2 vectors it returns the unnormalized distance between the vectors, the accumulated distance between them, the length of the warping path (the normalizing factor), and the warping path points.

To compare 2 vectors A and B call:
[Dist,D,k,w]=dtw(A,B)
Dist is the unnormalized distance
D is the accumulated distance
k is the length of the warping path
(the normalizing factor)
w is a matrix containing the points along the warping path

Comments and Ratings (48)

Qiang Yang

Hi Ethan, Sorry for something wrong of download link. I have changed that link to my Google Drive, so you can download it now:)

Ethan Berman

Hi Qiang Yang, I don't seem to be able to download the code from your website. Broken link? I am curious what changes you have made. Thanks.

Qiang Yang

hello everyone, maybe Timothy Felty forget to update this function.
I have modified this code to fix some BUGs and add some new functions according to those comments below.
you can download revised code at http://www.sunsetcity.cn/download/
contact me if you have any question.(email address in code)

q e

q e (view profile)

Jeff Court

Code worked great for me (R2014b). My data was of different lengths and didn't have an issue like another user.

My application was using pressure data to predict the path of the pressure sensor. I have additional visualization and computations folks can use if interested. Code expaination and download is here - http://blog.mide.com/dynamic-time-warping-to-estimate-location

saltfeig GAO

Megamind

Hi Grace Pan
Could you explain what your issue was?

Grace Pan

I have fixed my issue!

Grace Pan

Hi,Timothy Felty
Could i ask you a question? The code works perfectly when two input data have the same length. But if two input data have different length, such as [10 12 14 18 14 12 10 10 12 14 18 14 12 10] and [NaN 12 14 18 14 12 10 10 12 14 18 NaN NaN NaN], the output is NaN. Could you think how to deal with it?

Shuangjun

Good frame work, however ignoring the continuous condition.

Shuangjun

Good frame work, however ignoring the continuous condition.

in this code, how do i know if the two vectors are a good match or not..

arezoo

arezoo (view profile)

I ran this function for some series of data but all the time, the answer is the same... I mean for different data I get a fix D and Dist and etc.
am I wrong? or is there a problem with the function?

arezoo

arezoo (view profile)

anybody pleas answer and help me. I'm in a hurry

Qing

Qing (view profile)

Han

Han (view profile)

sai sahiti

Andrea Rollo

Hi everyone!!
I'm using this software, and I think that it's really useful.
But I've a question: how to use the normalization factor?
I've read that there are more users that have answered this, but I don't know how to read the previous answers.
Thanks a lot.

Tanmoy

Tanmoy (view profile)

please send complete code for melodic contour matching....

Vicky

Vicky (view profile)

He

He (view profile)

Mohammed

At least answer the previous questions!

Lars

Lars (view profile)

Maybe add code to ensure proper vectors, e.g. t=t(:)'; and r=r(:)'; in this case ;)

abdur

abdur (view profile)

im trying to compare two vectors of audio samples but the matrix dimensions dont match n d code gives error. plz assist

Nandha

Nandha (view profile)

Can I know how can I implement lower bounding (LB_keogh) and global constraint to this algorithm ?

Also, how to use obtain normalized distance using the normalizing factor ?

Mano Samuel

Hi Timothy,
could you let me know which article or book you used as a reference to code this ? . Thank you.
Mano

Wen

Wen (view profile)

should not be, d(n,m)=sqrt(sum((t(:,n)-r(:,m)).^2)); instead of d(n,m)=(t(n)-r(m))^2;
t, r are sequences of rows-dim vectors

Tony Mei

Can anyone explain how to use the normalizing factor? Thanks a lot.

Zhuo Feibao

Ahmed Bderhman

I think this is a good working and had help me more.

I have this question: i like to change euclidean distance{d=(repmat(Test',1,N)-repmat(Ref,M,1)).^2;} with mahalanobis distance is it possipole? if yes how can i do that?

because i like to test the efficiency of my system when i use euclidean distance and when i used mahalnobis distance.

Sai Man

Great code thanks for writing. But, I noticed a small discrepancy with my C code. In the .m file line 45:
min([D(n-1,m),D(n,m-1),D(n-1,m-1)]);

it would be much better to have the D(n-1,m-1) element in the first argument like this:
min([D(n-1,m-1),D(n,m-1),D(n-1,m)]);
and also swap the cases on the following lines.

This is because we are trying to find the minimum path length, and in the case where D(n-1,m-1)=D(n,m-1) or D(n-1,m-1)=D(n-1,m) then it would make sense to preference the diagonal element over the offdiagonal.

twinss ahmed

Pau Micó

I think it should be better to replace the sentence: w=cat(1,w,[n,m]); by: w=[n m; w];
In this way we get the w indexes in ascending order and it is easier to get t_warped and r_warped as: t_warped=t(w(:,1)); and r_warped=t(w(:,2));. In this way we can directly compare the warped sequences with the original ones without any index inversion.

weera kompreyaray

Sven Mensing

Good function
Another 10-fold Speed-up can be achived if you use a double-MIN construction for the Distance matrix

D(n,m)=d(n,m)+min(D(n-1,m),min(D(n-1,m-1),D(n,m-1)));

Boat MiMi

...

Yuzeng Lv

reza rezaww

Rogelio Ramos

Natan K

Can you tell me about speaker verification using mfcc and dtw. Please let me know.

jamal habibi

Ivo Ihrke

The loop

for m=2:m
D(1,m)=d(1,m)+D(1,m-1);
end

contains an error ( for statement ), should be:

for m=2:M
D(1,m)=d(1,m)+D(1,m-1);
end

If you want to compare vectors, where the vectors themselves are unknown, but their distance matrix is known, you can use your distance matrix instead of "d"

Georg Schmitz

The routine can be made 10 times faster by doing the d(n,m) calculation by

d=(repmat(t(:),1,M)-repmat(r(:)',N,1)).^2;

instead of the loop.

Carlos Franco

mahajan bhushan

zhlong l

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