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Linear Algebra/Inner Product Length and Orthogonality

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Orthogonality

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Cauchy-Schwarz inequality

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The Cauchy-Schwarz inequality states that the magnitude of the inner product of two vectors is less than or equal to the product of the vector norms, or: |⟨x,y⟩|≤‖x‖‖y‖.

Definition

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For any vectors x and y in an inner product space V, we say x is orthogonal to y, and denote it by x⊥y, if ⟨x,y⟩=0.

Orthogonal complement and matrix transpose

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Applications

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Linear least squares

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How to orthogonalize a basis

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Suppose to be on a vector space V with a scalar product (not necessarily positive-definite),
Problem: Construct an orthonormal basis of V starting by a random basis { v1, ... }.
Solution: Gram-Schmidt for non isotropic vectors, otherwise choose v_i + v_j and reiterate.