Hilbert Spaces and Orthogonal Projection in Infinite Dimensions
A complete inner-product space keeps the geometry of angles and projections when the dimension is infinite. Closest points to a closed subspace still exist and are unique, and every bounded functional is an inner product with a single fixed vector.
What a learner can do afterwards
- Project onto a closed subspace and check that the residual is orthogonal to it
- Expand a vector in an orthonormal basis and read off Parseval's identity
- State the Riesz representation theorem and say what it identifies with what
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A Hilbert space is an inner product space with one extra demand. Lengths and angles work as usual, and every sequence that ought to converge lands inside the space. That demand is called completeness, and it is what lets Fourier series converge to honest functions.
Take a closed subspace and any vector outside it. There is exactly one closest point in the subspace, and you check it with the residual test. Subtract the candidate from the vector: the leftover must sit at right angles to everything kept in the subspace.
An orthonormal basis lets you expand any vector as a sum of coefficients times basis vectors. Parseval reads the squared length straight from the coefficients: it equals the sum of their squared sizes. With coefficients 3 and 4, the squared length is 9 plus 16, which is 25.
Every bounded linear measurement on the space is an inner product in disguise. That is the Riesz claim: each such measurement pairs vectors with one single fixed vector. When you meet a new steady measurement, ask which fixed vector hides inside it.
Completeness keeps limits inside, projection gives the closest point with an orthogonal residual, and every steady measurement is an inner product.
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