Inner product space - minimization.

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SUMMARY

The discussion focuses on finding the linear polynomial g(t) that is nearest to the function f(t) = e^t in the vector space C[-1,1] of continuous real-valued functions, using the inner product defined by (f,g) = ∫_{-1}^{1} f(x)g(x) dx. The solution involves identifying orthogonal basis functions u1 and u2, specifically u1 = 1 and u2 = t, which span the subspace S within C[-1,1]. The goal is to minimize the integral of the difference between f(t) and g(t), simplifying the problem to finding the affine function that minimizes this integral.

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The question is : If the vector space C[1,1] of continuous real valued functions on the interval [1,1] is equipped with the inner product defined by (f,g)=^{1}_{-1} \intf(x)g(x)dx

Find the linear polynomial g(t) nearest to f(t) = e^t?


So I understand the solution will be given by (u1,e^t).||u1|| + (u2,e^t).||u2||

But I am having trouble understanding what u1 and u2 should be. I understand they must be othorgonal and basis for a subspace S \in C[-1,1].

However I am not too sure what dimension this basis should be of, and not 100% sure what is meant by the vector space C[-1,1].

(The solution uses 1 and t as u1 and u2...)

Many thanks in advance for any assistance.
 
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I think you're making it overcomplicated. Isn't it just asking for the affine function g(t) which minimises the integral for the given f(t)?
 

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