Publication | Closed Access
A survey of conjugate gradient algorithms for solution of extreme eigen-problems of a symmetric matrix
99
Citations
12
References
1989
Year
Numerical AnalysisMathematical ProgrammingSpectral TheoryVarious Conjugate GradientEngineeringFixed Symmetric MatrixSpectrum EstimationSemidefinite ProgrammingQuadratic OptimizationMatrix TheoryCg AlgorithmsMatrix MethodApproximation TheoryExtreme Eigen-problemsSymmetric MatrixInverse ProblemsComputer ScienceMatrix AnalysisSignal ProcessingConic OptimizationSpectral AnalysisConjugate Gradient Algorithms
A survey of various conjugate gradient (CG) algorithms is presented for the minimum/maximum eigen-problems of a fixed symmetric matrix. The CG algorithms are compared to a commonly used conventional method found in IMSL. It is concluded that the CG algorithms are more flexible and efficient than some of the conventional methods used in adaptive spectrum analysis and signal processing.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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