numerical-linear-algebra-toolkit

# Numerical Linear Algebra Toolkit ## Purpose Provides high-performance numerical linear algebra operations for scientific computing and mathematical analysis. ## Capabilities - Matrix decompositions (LU, QR, SVD, Cholesky, Schur) - Eigenvalue/eigenvector computation - Sparse matrix operations - Iterative solvers (CG, GMRES, BiCGSTAB) - Condition number estimation - Error analysis and bounds ## Usage Guidelines 1. **Decomposition Selection**: Choose appropriate factorization for the problem 2. **Sparsity Exploitation**: Use sparse formats for large sparse matrices 3. **Iterative Methods**: Apply iterative solvers for very large systems 4. **Conditioning**: Assess and monitor condition numbers ## Tools/Libraries - LAPACK - BLAS - SuiteSparse - Eigen