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Compare two vectors for similarity

Souparno Bandyopadhyay さんによって質問されました 2012 年 12 月 9 日
How to compare two vectors quickly. Right now I print out each in a loop and examine them by eye, is there a way i can find if two are almost similar.

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Souparno Bandyopadhyay 2012 年 12 月 9 日
I am comparing A to B and then A to C, I need a single number that will allow me to quickly judge A resembles B or C.

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Login_Name
回答者: Login_Name
2012 年 12 月 9 日
 採用された回答

What is the criteria for 'almost similar' in your application? 90% same exact values? 90% of the values in one vector within 95% of some other value in the other vector? Do the values have to be in the same positions? Do the vectors have to be the same length? Perhaps a few short examples would help...

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Souparno Bandyopadhyay 2012 年 12 月 9 日
I am using lpc(x,4), x is a set of discrete data to get 4 coeff vector of a linear prediction filter. Then I am comparing these coeff to another set that i get from executing lpc over another part of the same x(n) to find which two parts resemble the closest.
Jan
2012 年 12 月 9 日
@Souparno: Accepting an answer means that the problem is solved. Is this true here?
Souparno Bandyopadhyay 2012 年 12 月 10 日
yes, S = sum(A-B), is what I was looking for.

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Greg Heath
回答者: Greg Heath
2012 年 12 月 10 日

S = sum(A-B) is NOT a useful function for quantifying similarity because positive and negative terms will cancel.
The most common are
mae(A-B) % mean(abs(A-B))
sae(A-B) % sum(abs(A-B))
norm(A-B,1) % sum(abs(A-B))
norm(A-B,inf) % max(abs(A-B))
mse(A-B) % mean((A-B).^2)
sse(A-B) % sum((A-B).^2)
norm(A-B) % sqrt(sse(A-B))
Hope this helps.
Thank you for formally accepting my answer
Greg

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