Solution

ID: past-exam-of-the-approximation-of-functions-course-of-the-university-of-oxford/2011/2/b/solution

Put in the weighted inner product. Since ,
The last equality follows by the product-to-sum trigonometric identity and integration. Thus these are nonzero mutually orthogonal polynomials. The first are linearly independent, and the vector space has dimension ; therefore .
For any , the function of the real parameter
has a minimum at . Its derivative there vanishes, proving . This is precisely the defining orthogonality of an orthogonal projection, or a least-squares polynomial in an orthogonal-polynomial basis. Conversely, this condition and the Pythagorean theorem for inner product spaces give , proving the minimum and its uniqueness.
Expand in the basis already established and take the inner product with . Orthogonality leaves , so
In particular and for . These are the corresponding Chebyshev series coefficients with the constant coefficient convention used in this question.

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