Proving the Pythagorean Theorem for Inner Product Spaces

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Homework Help Overview

The discussion revolves around proving the inequality ||v|| >= ||proj(u)v|| in the context of inner product spaces, specifically for finite-dimensional subspaces U. The original poster expresses confusion about how to begin the proof and references the Pythagorean theorem as a hint.

Discussion Character

  • Exploratory, Assumption checking, Conceptual clarification

Approaches and Questions Raised

  • Participants discuss the projection of a vector onto a subspace and the implications of the Pythagorean theorem. Some suggest expanding the expressions for the left and right sides of the inequality, while others question the clarity of the problem statement and the definitions used.

Discussion Status

There is ongoing exploration of the problem, with participants attempting to clarify the setup and definitions. Some have offered insights into the nature of projections and the relationship between the components of vectors in the context of inner product spaces. However, there is no explicit consensus on the approach to take.

Contextual Notes

Participants note potential confusion regarding the notation and definitions in the original problem statement, particularly concerning the vector spaces involved and the nature of the projection. There are also mentions of using orthonormal bases to simplify the expressions.

playboy
A question reads:

Let V be a vector in an inner product space V

show that ||v|| >= ||proj(u) v|| holds for all finitie dimensional subspaces of U.

Hint: Pythagorean theorem.

Okay... where on Earth do i begin?

I thought perhaps I should expand the RIGHT side of the equation, but that dosn't seem to be getting me anywhere really.

The LEFT side seems pretty useless too, so I am stuck trying to show that the RIGHT side is >= ...

anybody have any ideas?

Thanks
 
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playboy said:
A question reads:
Let V be a vector in an inner product space V
show that ||v|| >= ||proj(u) v|| holds for all finitie dimensional subspaces of U.
Hint: Pythagorean theorem.
Okay... where on Earth do i begin?
I thought perhaps I should expand the RIGHT side of the equation, but that dosn't seem to be getting me anywhere really.
The LEFT side seems pretty useless too, so I am stuck trying to show that the RIGHT side is >= ...
anybody have any ideas?
Thanks
Do you mean
[itex]\vec{V}[/itex] is a vector in an inner product space [itex]U[/itex]?
otherwise that doesn't make sense?
Maybe you can find some easy cases, and work from there?
 
If you draw these two vectors out, it should be very obvious. The magnitude of the projection is just the component:

[tex]\left|\text{proj}_{u}v\right|=\frac{\left(u,v\right)}{u}[/tex]

...which is really just saying v*cosθ. What do you know about the cosine function? Well, for one, it is less than or equal to 1 for all values of θ. Does this help?
 
apmcavoy : There are no "two vectors". A vector v in U is being projected onto some subspace (W, say) of U. However, with some additional construction, your method would work.

playboy : Call the subspace W, and write the projection down in terms of the basis vectors [itex]w_i[/itex] of W. similarly write down the expansion of the norm in terms of the basis vectors [itex]u_i[/itex] of U.

What do you know about these two sets of basis vectors ?
 
Last edited:
okay thanks for the help everyone!

Gokul43201: ill try your metod and get give back my results!
 
Now i am even more lost than ever :S

For the RHS...i get...

<v, w1> + <v, w2> + ...
||w1||...||w2||

For the left hand side...

<u,u>^0.5

Am i on the right track?
 
First, we need to confirm that we're all solving the same problem. Where did U come from. Did you mean to write (in the OP) : "...for all finite dimensional subspaces U of the space V" ?
playboy said:
Now i am even more lost than ever :S
For the RHS...i get...
<v, w1> + <v, w2> + ...
||w1||...||w2||
The length (or norm) is not equal to the sum of its components.

[tex]proj_U(v) = \sum _{i=1}^k \langle v,w_i \rangle w_i[/tex]

[tex]\implies ||proj_U(v)|| = \sqrt{\sum _{i=1}^k \langle v,w_i \rangle ^2}[/tex]

For the left hand side...
<u,u>^0.5
Am i on the right track?
Expand ||v|| similarly.
 
Noooo... this is why its not making sense.

Isn't the projection...

<v wi>
______ wi
<wi wi>


and not


<v wi> wi



And on the LHS... (v is just a vecotr)
so ||v|| = (v1^2 + v2^2 + ... + vn^2)^0n5
 
Gokul43201 said:
apmcavoy : There are no "two vectors". A vector v in U is being projected onto some subspace (W, say) of U. However, with some additional construction, your method would work.

playboy : Call the subspace W, and write the projection down in terms of the basis vectors [itex]w_i[/itex] of W. similarly write down the expansion of the norm in terms of the basis vectors [itex]u_i[/itex] of U.

What do you know about these two sets of basis vectors ?
Yes, right. I'm sorry if that confused anyone who read this. I guess I was just assuming some vector u in U.
 
  • #10
playboy said:
Noooo... this is why its not making sense.
Isn't the projection...
<v wi>
______ wi
<wi wi>
and not
<v wi> wi
If [itex]w_i[/itex] is a basis vector, what's [itex]\langle w_i,w_i \rangle[/itex] ?
And on the LHS... (v is just a vecotr)
so ||v|| = (v1^2 + v2^2 + ... + vn^2)^0n5
What are v1, v2, etc ?

PS : Why are you not addressing the problem that no one really knows what the actual question is? The question as stated in the OP is incorrect and needs to be fixed.
 
Last edited:
  • #11
The Question Reads:

Let v be a vector in an inner product space V

show that ||v|| >= ||proj u (v)|| holds for all finitie dimensional subspaces of U.

Hint: Pythagorean theorem.
_____________________________________________
how i approached it:

Let (e1,...,en) be an orthonognal basis:

||proj u (V)||^2 = <proj u (V), proj u (V)>
||proj u (V)|| = ( <v e1>^2/<e1 e1> + ... + <v en>^2/<en en>)^0.5

Note that i did not show my full computation from the beginning, that would
just be too long to type out.

and ||v|| = (v1^2 + ... + Vn^2)^0.5 since v is a Vector

Im lost after this point :( Please help
 

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