Use the real inner product
Orthogonality means this integral is zero for any two distinct listed functions. The individual squared norms are positive: the constant function has squared norm , while every listed sine or cosine has squared norm . Thus they are orthogonal but not normalized to unit length in this inner product.
Take the inner product of the Fourier series with . Fourier orthogonality eliminates the constant, all cosine terms, and all sine terms except the th. The remaining squared norm is
so
For a square-integrable function, the calculation is justified by taking inner products of finite Fourier partial sums and passing to their mean-square limit.
The analogous orthogonal projection onto the cosine terms gives
For , this means ; the actual constant in the Fourier series is because the constant function has squared norm .
Let be the Fourier partial sum through frequency . By orthogonality and the coefficient formulas,
Expanding the nonnegative squared L2 norm of the error gives the exact finite identity
For in the L2 space, completeness of the Fourier basis makes the left-hand side tend to zero. Dividing the resulting equality by proves Parseval's identity:
This argument uses convergence in L2 rather than an unqualified exchange of an infinite sum with the integral of its square. The function in part (c) is continuous and piecewise polynomial, so these hypotheses hold.
The function is an odd function, so . Here , and the Fourier coefficients are
Write . One integration by parts has zero endpoint terms because vanishes at both endpoints:
A second integration by parts gives
Therefore , zero for even and for odd . The Fourier series is
The coefficients are absolutely summable, and the periodic function is continuous even at the joins , so the displayed Fourier series represents it everywhere.
The square is even, and direct integration gives
Using the nonzero Fourier coefficients in Parseval's identity,
Hence

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