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From: "Fatih " <fatih.arslan.koc@gmail.com>
Newsgroups: comp.soft-sys.matlab
Subject: Re: Distance between two distributions
Date: Tue, 14 Apr 2009 13:29:01 +0000 (UTC)
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Alex Zak <zak.alex@gmail.com> wrote in message <97162316-c571-47e3-a40d-5d7a0a94f88a@i24g2000prf.googlegroups.com>...
> On Jan 31, 12:44=A0am, Greg Heath <he...@alumni.brown.edu> wrote:
> > On Jan 31, 12:00=A0am, Greg Heath <he...@alumni.brown.edu> wrote:
> >
> > > On Jan 30, 4:26 pm,AlexZak<zak.a...@gmail.com> wrote:
> >
> > > > What is the best criteria to measure distance between two independent
> > > > normal distributions using Matlab??
> >
> > > > Thanks.
> >
> > > 1. Mahalanobis distance for linear classifiers is proportional to
> >
> > > (m2-m1)' * inv( (C1 + C2)/2 ) * (m2-m1)
> >
> > > 2. Bhattycharya (Bhattacharya?) distance for linear and quadratic
> > > classifiers is proportional to
> >
> > > (m2-m1)' * ( ( inv(C1) + inv(C2) )/2 ) * (m2-m1)
> >
> > BZZT!
> >
> > Sorry, that is proportional to a term in the quadratic classifier
> > discriminant.
> >
> > Seehttp://en.wikipedia.org/wiki/Bhattacharyya_coefficient
> >
> > which yields
> >
> > (1/8) * (m2-m1)' * inv( (C1 + C2)/2 ) * (m2-m1)
> >
> > + (1/2) * ln( det(C) / sqrt( det(C1) * det(C2) )
> >
> > > See Devijver and Kittler (1981?) for a comprehensive discussion of
> > > separability measures.
> >
> > > More info is available in comp.ai.neural-nets.
> >
> > Hope this helps.
> >
> > Greg
> 
> Thanks

I also will use a distance metric between two distributions. But my problem is that these two distributions contain noise wihich is rayleigh distributed. So how can i adapt the distance metric to rayleigh?