# Linear dependence and inner product space

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## Homework Statement

The following is from the book Linear Algebra 3rd Edn by Stephen Friedberg, et al:
pg 327 said:
Let V be an inner product space, and let S be an orthogonal set of nonzero vectors. Then S is linearly independent. Proof:

Suppose that $$v_1, \ ... \,v_k \in S$$ and $$\sum_{i=1}^k a_i v_i = 0$$

By theorem 6.3, aj = $$\langle 0,v_j \rangle / ||v_j||^2 = 0$$ for all j. So S is linearly independent.
Here aj are scalars of field F and vj are vectors of inner product space V.

## Homework Equations

Theorem 6.3:
Let V be an inner product space, and let S = {v1, ... , vk} be an orthogonal set of non-zero vectors. If $$y = \sum^k_{i=1} a_i v_i$$ then $$a_j = \langle y, v_j \rangle / ||v_j||^2$$ for all j

## The Attempt at a Solution

Now I don't understand why theorem 6.3 implies aj = 0 = $$\langle 0,v_j \rangle / ||v_j||^2$$ for all j. I can see how this is zero if the numerator $$\langle 0,v_j \rangle$$ = 0, but the inner product isn't even defined yet and I don't see anywhere in the axioms that the inner product of the zero vector and an orthogonal vector would always be zero. So how does theorem 6.3 apply here?

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CompuChip
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[...] the inner product isn't even defined yet
I find that hard to believe, since I don't see how you can talk about an inner product space without having defined an inner product :)
So I guess you should go back a bit and find that definition and you will see that it immediately follows from the properties of an inner product that <v, 0> = 0 for all v. For example:
• Let x be any vector, then <v, 0> = <v, 0*x> (see definition of vector space) = 0 * <v, x> (by linearity of the inner product) = 0 (by multiplicative properties of the reals )
• <v, 0> = <v, v - v> (by definition of the vector space) = <v, v> + <v, -v> (by additivity of the inner product) = <v, v> - <v, v> = 0. Of course, technically, v - v = v + (-v) with the existence of -v asserted by the definition of vector space, etc.

Homework Helper
I find that hard to believe, since I don't see how you can talk about an inner product space without having defined an inner product :)
Well I meant the specific inner product function, not the general notion of an inner product on a vector space.
• Let x be any vector, then <v, 0> = <v, 0*x> (see definition of vector space) = 0 * <v, x> (by linearity of the inner product) = 0 (by multiplicative properties of the reals )
This is just what I need. Thanks!