A Shamanskii-Like acceleration scheme for nonlinear equations at singular roots
Mathematics of Computation
Inexact trust region method for large sparse systems of nonlinear equations
Journal of Optimization Theory and Applications
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SIAM Journal on Numerical Analysis
Tensor Methods for Large, Sparse Nonlinear Least Squares Problems
SIAM Journal on Scientific Computing
Historical developments in convergence analysis for Newton's and Newton-like methods
Journal of Computational and Applied Mathematics - Special issue on numerical analysis 2000 Vol. IV: optimization and nonlinear equations
Practical quasi-Newton methods for solving nonlinear systems
Journal of Computational and Applied Mathematics - Special issue on numerical analysis 2000 Vol. IV: optimization and nonlinear equations
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Journal of Computational and Applied Mathematics - Special issue: Proceedings of the 9th International Congress on computational and applied mathematics
Sequential estimation techniques for quasi-newton algorithms.
Sequential estimation techniques for quasi-newton algorithms.
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Journal of Computational and Applied Mathematics
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SIAM Journal on Optimization
On the Relationship between the Convergence Rates of Iterative and Continuous Processes
SIAM Journal on Optimization
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Journal of Computational and Applied Mathematics
Applied Numerical Mathematics - 6th IMACS International symposium on iterative methods in scientific computing
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Quasi-Newton methods for solving singular systems of nonlinear equations are considered in this paper. Singular roots cause a number of problems in implementation of iterative methods and in general deteriorate the rate of convergence. We propose two modifications of QN methods based on Newton's and Shamanski's method for singular problems. The proposed algorithms belong to the class of two-step iterations. Influence of iterative rule for matrix updates and the choice of parameters that keep iterative sequence within convergence region are empirically analyzed and some conclusions are obtained.