QR Decomposition
Decomposition & Spectral Methods DS practice problem on Onlearn.
Difficulty: medium.
Topics: Understanding QR Decomposition via Gram-Schmidt Orthogonalization, Gram-Schmidt Process, Vector Normalization, Projection onto Subspaces, Upper Triangular Matrix Construction, Floating Point Stability, Linear Algebra, Matrix Factorization, Numerical Analysis, Vector Spaces, Computational Methods, Orthogonalization, Orthonormal Basis, Projection Operators, Inner Product Spaces, Triangular Systems.
Implement the Classical Gram Schmidt process to decompose a given non singular square matrix A into an orthogonal matrix Q and an upper triangular matrix R such that A = QR.