How Do I Calculate Inner Product in Gram-Schmidt Procedure for Polynomial Basis?

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In summary, the question is asking to use the Gram-Schmidt procedure to construct an orthonormal basis for P2 from the basis {1,t,t2}. The first step is to normalize the first vector, e1=1/sqrt(3). Then, using the formula v_{j+1}:=u_{j+1}-\sum_{i=1}^{j}<u_{j+1},e_{i}>e_{i}, we can find e2=t/sqrt(2) and e3=-1/sqrt(3). Finally, we must normalize e3 to get the orthonormal basis for P2.
  • #1
boneill3
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Homework Statement



We consider P2 the vector space of all real polynomials of degree at most 2.

<f,g> = [itex]f(-1)g(-1)+f(0)g(0)+f(1)g(1)[/itex]

Use the Gram-Schmidt procedure to construct an orthonormal basis for P2 from the basis {1,t,t2}

Homework Equations



[itex]
v_{j+1}:=u_{j+1}-\sum_{i=1}^{j}<<u_{j+1},e_{i}>>e_{i}[/itex]

[itex]
e_1 = \frac{u_1}{||u_{1}|| }[/itex]

The Attempt at a Solution



I have a basis [itex] u_1 = 1, u_2 = t, u_3 = t^2[/itex]

so

[itex]
e_1 = \frac{u_1}{||u_{1}|| }[/itex]

[itex]
e_1 = \frac{1}{\sqrt{2}} [/itex]


is the next step

[itex]
v_{2}:=u_{2}-\sum_{i=1}^{j}<<u_{2},e_{i}>>e_{i}[/itex]

[itex]= t - << t,\frac{1}{\sqrt{2}} >>\frac{1}{\sqrt{2}}[/itex]


My question is how do I calculate the inner product [itex]<< t,\frac{1}{\sqrt{2}} >>[/itex]
do I need to plug in the value of f(t) into

<f,g> = [itex]f(-1)g(-1)+f(0)g(0)+f(1)g(1)[/itex]

and does g() become [itex]
g(e_1) = g(\frac{1}{\sqrt{2}}) [/itex]


regards
 
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  • #2
The inner product <<t,1/sqrt(2)>>=(-1)/sqrt(2)+0/sqrt(2)+(1)/sqrt(2). That's what you definition says, isn't it? g is a constant.
 
  • #3
So

[itex]v_{2}:=u_{2}-\sum_{i=1}^{j}<u_{j+1},e_{i}>e_{i}[/itex]

[itex]= t - << t,\frac{1}{\sqrt{2}} >>\frac{1}{\sqrt{2}}[/itex]

[itex]= t - (\frac{-1}{\sqrt(2)}+\frac{0}{\sqrt(2)}+\frac{1}{\sqrt(2)}) \frac{1}{\sqrt{2}}[/itex]

[itex]= t - (0) \frac{1}{\sqrt{2}}[/itex]

[itex]v_{2}:= t[/itex]




for v3: do I substitute [itex]v_{2}:= t[/itex] from above for [itex]e_{2}[/itex]
in the next equation? or do I need to nomalise it first



[itex]v_{3}:=u_{3}-\sum_{i=1}^{j}<u_{j+1},e_{i}>e_{i}[/itex]

[itex]= t^2 - (<< t^2,e_{2} >>e_{2}) + (<< t,\frac{1}{\sqrt{2}} >>\frac{1}{\sqrt{2}})[/itex]

[itex]= t^2 - (<< t^2,t >>t) + (<< t,\frac{1}{\sqrt{2}} >>\frac{1}{\sqrt{2}})[/itex]


or

[itex]= t^2 - (<< t^2,1 >>1) + (<< t,\frac{1}{\sqrt{2}} >>\frac{1}{\sqrt{2}})[/itex]


regards
 
Last edited:
  • #4
That last equation was using [itex](\frac{1}{t})t= 1[/itex]
as [itex]e_{2}[/itex]
 
  • #5
t is orthogonal to e1=1/sqrt(2) (i.e. <t,1/sqrt(2)>=0). But it's not normalized. <t,t> is not one. Normalize it. Then that becomes e2. Then find u3=t^2-(<t^2,e1>e1+<t^2,e2>e2) and normalize u3. Your are getting your functions all mixed up in the Gram-Schmidt process.
 
  • #6
BTW before you go any further <1,1>=3. So the normalization of 1 isn't 1/sqrt(2). It's 1/sqrt(3). Sorry, I missed that.
 
  • #7
Thanks

So

[itex]v_{2}:= t[/itex]
therefore

[itex]e_{2} = \frac{t}{||v_2|| }v_2[/itex]
[itex]e_{2} = \frac{t}{\sqrt{-1^2+0^2+1^2}}[/itex]
[itex]e_{2} =\frac{1}{\sqrt{2}}[/itex]

is that right ?
 
  • #8
beetle2 said:
Thanks

So

[itex]v_{2}:= t[/itex]
therefore

[itex]e_{2} = \frac{t}{||v_2|| }v_2[/itex]
[itex]e_{2} = \frac{t}{\sqrt{-1^2+0^2+1^2}}[/itex]
[itex]e_{2} =\frac{1}{\sqrt{2}}[/itex]

is that right ?

Is boneill3 the same person as beetle2? If so the Forum doesn't allow really allow you to use two different user pseudonyms. If you are, please stick with one, ok? Otherwise I should report this. If you aren't you are doing exactly the same kind of notational confusion as boneill3. If v2=t, then e2=v2/||v2||=t/||t|| which is t/sqrt(2). Not 1/sqrt(2).
 
  • #9
Hi,
Sorry I had to log in from another computer.

I found u3=t^2-(<t^2,e1>e1+<t^2,e2>e2) to equal

t^2-(1/sqrt(3)(1/sqrt(3)+1/sqrt(3)) + t/sqrt(2) (t/sqrt(2)+ t/sqrt(2))

= t^2 - (2/3+t^2)

u3 = -2/3

does normalising make it e3= -(2/3) / sqrt((-2/3)^2 +(-2/3)^2+(-2/3)^2)

e3 = -1/sqrt(3)
 
  • #10
I think i'll make it clearer
I found
[itex]u3=t^2-(<t^2,e_1>e_1+<t^2,e_2>e_2) [/itex]
to equal

[itex]t^2-(\frac{1}{\sqrt{3}})(\frac{1}{\sqrt{3}}+\frac{1}{\sqrt{3}}) + (\frac{t}{\sqrt{2}}) (\frac{t}{\sqrt{2}}+\frac{t}{\sqrt{2}})

= t^2 - (\frac{2}{3}+t^2)

= \frac{-2}{3} [/itex]
does normalising make it

[itex]e_{3}= \frac{\frac{-2}{3}}{{\sqrt{(\frac{-2}{3})^2 +(\frac{-2}{3})^2+(\frac{-2}{3})^2}}}[/itex]

[itex]e_{3} = \frac{-1}{\sqrt{3}}[/itex]
 
  • #11
If that whole thing had worked then you should be able to check that <e1,e3>=0. It's not zero. The inner product of two functions of t, <f(t),g(t)>, should always be a number, not another function of t. Try computing <t^2,t/sqrt(2)> again.
 
  • #12
So,

to compute <t^2,t/sqrt(2)>

we have

[itex]\left[(-1)^2(\frac{-1}{\sqrt{2}})+](0)^2(\frac{0}{\sqrt{2}})+](1)^2(\frac{1}{\sqrt{2}})\right][/itex]

therfore

[itex]t^2-(\frac{1}{\sqrt{3}})(\frac{1}{\sqrt{3}}+\frac{1}{\sqrt{3}}) + (\frac{t}{\sqrt{2}}) (0)
= t^2 - (\frac{2}{3}) [/itex]
 
  • #13
Ok, now you just have to normalize t^2-(2/3).
 
  • #14
I normalised u3 and got

[itex]e_{3}= \frac{t^2-\frac{-2}{3}}{\sqrt{\frac{2}{3}}}[/itex]

I checked that <e1,e3>=0 which it does.

Thanks so much for your help
 

FAQ: How Do I Calculate Inner Product in Gram-Schmidt Procedure for Polynomial Basis?

What is the Gram-Schmidt Procedure?

The Gram-Schmidt Procedure is a mathematical technique used to convert a set of linearly independent vectors into an orthonormal basis. This is useful in many applications, including solving systems of linear equations and performing projections in vector spaces.

How does the Gram-Schmidt Procedure work?

The procedure involves taking a set of linearly independent vectors and systematically transforming them into an orthonormal set by subtracting out their projections onto previously constructed vectors. This ensures that each new vector is orthogonal to all previously constructed vectors, resulting in an orthonormal basis.

Why is the Gram-Schmidt Procedure important?

The Gram-Schmidt Procedure is important because it allows for the simplification of many mathematical problems involving vectors. By converting a set of vectors into an orthonormal basis, calculations such as finding distances and projections become much easier.

What are some applications of the Gram-Schmidt Procedure?

The Gram-Schmidt Procedure has many applications in mathematics, physics, and engineering. It is commonly used in linear algebra, signal processing, and computer graphics, among others. It is also a fundamental tool in the study of vector spaces and inner product spaces.

Are there any limitations to the Gram-Schmidt Procedure?

While the Gram-Schmidt Procedure is a powerful tool, it does have some limitations. It is only applicable to finite-dimensional vector spaces and may not work for certain sets of vectors that are close to being linearly dependent. In addition, it can be computationally expensive for large sets of vectors.

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