1956
DOI: 10.2307/2001916
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A Method for Solving Algebraic Equations Using an Automatic Computer

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Cited by 486 publications
(123 citation statements)
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“…(10) using the Müller method (Muller 1956) to find the complex roots at fixed input parameters η = 0.01 and b = 0.36, and varying Alfvén-Mach numbers M A from zero to some reasonable numbers. Before starting any numerical procedure for solving the aforementioned dispersion equation, we note that for each input value of M A one can get two c k -dispersion curves one of which (for relatively small magnitudes of M A ) has a normalised phase velocity roughly equal to M A − 1 and a second dispersion curve associated with dimensionless phase velocity equal to M A + 1.…”
Section: Kink Wavesmentioning
confidence: 99%
“…(10) using the Müller method (Muller 1956) to find the complex roots at fixed input parameters η = 0.01 and b = 0.36, and varying Alfvén-Mach numbers M A from zero to some reasonable numbers. Before starting any numerical procedure for solving the aforementioned dispersion equation, we note that for each input value of M A one can get two c k -dispersion curves one of which (for relatively small magnitudes of M A ) has a normalised phase velocity roughly equal to M A − 1 and a second dispersion curve associated with dimensionless phase velocity equal to M A + 1.…”
Section: Kink Wavesmentioning
confidence: 99%
“…(48) requires an initial guess, Q (1) d (z), which we will describe later. It is hoped as we iterate through i finding a minimum of (48), then the differences between the values of …”
Section: Methods Of Nonlinear Least Squaresmentioning
confidence: 99%
“…x min < ; (12) where x min is that x (k) leading to the minimum jP(x)j up to the actual iteration step and again depends on the computer accuracy. In the case of a real valued polynomial (i.e., all p are real) for every complex root also its complex conjugate is a root which can be de ated together.…”
Section: Newton's Methodsmentioning
confidence: 99%