Innner products and basis representation

In summary, the sum of the i=0 to n orthonormal vectors in a vector space is equal to the product of the i=0 to n individual vectors.
  • #1
iontail
24
0
hi, I have a quickon vector spaces.

Say for example we have


X = a1U1 + a2U2 ...anUn
this can be written as

X = sum of ( i=0 to n) ai Ui


now how can I get and expression of ai in therms of X and Ui.

do we use inner product to do this...ans someone please explain how to go forward.
 
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  • #2
If the Ui basis is "orthonormal" then, taking the inner product of X with Uk gives [itex]<X, U_n]>= a_1 <U_1,U_k>+ \cdot\cdot\cdot+ a_k<U_k,U_k>+ \cdot\cdot\cdot+ a_n<U_n, U_k>= a_1(0)+ \cdot\cdot\cdot+ a_k(1)+ \cdot\cdot\cdot+ a_n(0)= a_k[/itex].

That is, for an orthonormal basis, [itex]a_k= <X, U_k>[/itex]. If the basis is NOT orthonormal, there is no simple formula. That's why orthonormal bases are so popular!
 
  • #3
the basis is orthonormal...so the solution you suggested should be ok...however i don't have latex and have never used it before so can't view your reply. do I just downlad latex to view the thread or do I have to do something else.
 
  • #4
thanks for the reply...as well.
 
  • #5
LaTeX

iontail said:
...however i don't have latex and have never used it before so can't view your reply. do I just downlad latex to view the thread or do I have to do something else.

Hi iontail! :smile:

You don't need to "have" LaTeX, it should be visible anyway.

There's just something wrong with that particular LaTeX …I can't read it either :rolleyes:

(I can't see what's wrong with the code though.)

To see the original code, just click on the REPLY button. :wink:
 
  • #6
Here is what HallsofIvy want to write:

[tex]<X, U_n]>= a_1 <U_1,U_k>+ \cdot\cdot\cdot+ a_k<U_k,U_k>+ \cdot\cdot\cdot+ a_n<U_n, U_k>= a_1(0)+ \cdot\cdot\cdot+ a_k(1)+ \cdot\cdot\cdot+ a_n(0)= a_k[/tex]
 

FAQ: Innner products and basis representation

What is an inner product?

An inner product is a mathematical operation that takes two vectors and produces a scalar value. It is often used in linear algebra and functional analysis to measure the similarity or angle between two vectors.

How is an inner product different from a dot product?

An inner product is a more general concept than a dot product. While a dot product is limited to vectors in Euclidean space, an inner product can be defined for vectors in any vector space. Additionally, an inner product can take complex values, while a dot product only produces real values.

What is a basis representation?

A basis representation is a way of expressing a vector in terms of a set of basis vectors. These basis vectors form a basis for the vector space and can be used to uniquely represent any vector in that space. This is similar to representing a point in 3D space using the x, y, and z coordinates.

How is an inner product used in basis representation?

An inner product is used to calculate the coefficients of a vector in terms of the basis vectors. By taking the inner product of a vector with each basis vector, we can determine how much of each basis vector is needed to represent the original vector.

Can any set of vectors be used as a basis for a vector space?

No, a set of vectors can only form a basis for a vector space if they are linearly independent and span the entire vector space. This means that none of the vectors can be expressed as a linear combination of the others, and together they can represent any vector in the space.

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