mnb96
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Hello.
Let´s suppose we are given two subspaces of [tex]\mathbb{R}^n[/tex] that have dimension k, where [itex]1\leq k<n[/itex]. I think they are called grassmanians.
How can I compute a "distance" between two different k-subspaces?
my attempt to a solution:
As a toy example, for n=2 and k=1 we can use the minimum angle between the unit-vectors u and v:
[tex]d(u,v)=\frac{|<u,v>|}{|u||v|}[/tex]
In order to extend this to more dimensions I used the definition of scalar product used in Geometric (Clifford) Algebra, which is:
[tex]\ast : \wedge\mathbb{R}^n \times \wedge\mathbb{R}^n \rightarrow \mathbb{R}[/tex]
[tex]A\ast B=(a_1\wedge\ldots\wedge a_k)\ast(b_1\wedge\ldots\wedge b_m)=det[m_{ij}][/tex] ; for [tex]k=m[/tex]
[tex]A\ast B=0[/tex] ; for [tex]k\neq m[/tex]
where the (i,j) element of that matrix is [tex]m_{ij}=<a_i,b_j>[/tex].
Is that correct?
Let´s suppose we are given two subspaces of [tex]\mathbb{R}^n[/tex] that have dimension k, where [itex]1\leq k<n[/itex]. I think they are called grassmanians.
How can I compute a "distance" between two different k-subspaces?
my attempt to a solution:
As a toy example, for n=2 and k=1 we can use the minimum angle between the unit-vectors u and v:
[tex]d(u,v)=\frac{|<u,v>|}{|u||v|}[/tex]
In order to extend this to more dimensions I used the definition of scalar product used in Geometric (Clifford) Algebra, which is:
[tex]\ast : \wedge\mathbb{R}^n \times \wedge\mathbb{R}^n \rightarrow \mathbb{R}[/tex]
[tex]A\ast B=(a_1\wedge\ldots\wedge a_k)\ast(b_1\wedge\ldots\wedge b_m)=det[m_{ij}][/tex] ; for [tex]k=m[/tex]
[tex]A\ast B=0[/tex] ; for [tex]k\neq m[/tex]
where the (i,j) element of that matrix is [tex]m_{ij}=<a_i,b_j>[/tex].
Is that correct?