For independent columns in a real inner product space, the Gram-Schmidt process recursively formsEach subtracts the orthogonal projections onto earlier normalized vectors. Their independence ensures . The resulting are orthonormal and preserve the span of every initial column set. Putting and for , with zeros below the diagonal, gives a QR decomposition with . Dependent input columns require omitting a zero residual or treating rank deficiency separately.
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