SIAM Journal on Matrix Analysis and Applications · 1995 · 62 citations · 16 references
ComputingComputer ScienceMathematicsAlgorithmsOptimizationScientific ComputingMatrix ComputationMatrix FactorizationMatrix SystemsNumerical AlgorithmsNumerical AnalysisNumerical Linear AlgebraCholesky DecompositionComputational Matrix TheoryDisplacementLow-rank Matrix FactorizationNumerical SimulationNumerical Stability AnalysisReflection Coefficients
This paper contains a numerical stability analysis of factorization algorithms for computing the Cholesky decomposition of symmetric positive definite matrices of displacement rank 2. The algorithms in the class can be expressed as sequences of elementary downdating steps. The stability of the factorization algorithms follows directly from the numerical properties of algorithms for realizing elementary downdating operations. It is shown that the Bareiss algorithm for factorizing a symmetric positive definite Toeplitz matrix is in the class and hence the Bareiss algorithm is stable. Some numerical experiments that compare behavior of the Bareiss algorithm and the Levinson algorithm are presented. These experiments indicate that generally (when the reflection coefficients are not all of the same sign) the Levinson algorithm can give much larger residuals than the Bareiss algorithm.
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