The authors cover iterative methods
for the solution of systems of linear equations, conjugate gradient methods, and solutions of systems of linear equations, and many other related subjects.
In recent years, numerous higher order iterative methods
have been developed and analyzed for solving nonlinear equations that improve classical methods such as Newton's, Chebyshev, Chebyshev-Halley's, etc.
Kelley, Iterative Methods
for Linear and Nonlinear Equations, Frontiers in Applied Mathematics, Philadelphia, Pa, USA, 1995.
This paper is concerned with the development of fast iterative methods
for the numerical solution of linear partial differential equation.
This improvement plays an important role in all iterative methods
, like monotone method, generalized monotone methods etc.
Several forms of Newton's iterative methods
are discussed by (Stoer and Bulirsch, 2013 and Ben, 1997).
A good choice in last case are iterative methods
like Newton, Conjugate Gradient, Broyden, etc.
obtained by suitably discretizing ill-posed operator equations that model many inverse problems arising in various scientific and engineering applications generally requires the use of iterative methods
At the present time for positioning and orientation tasks under precise control of modern industrial robots using analytical and numerical iterative methods
are suitable for large scale linear equations.
We present the most widely used iterative methods
for nonlinear equations and MATLAB features for finding numerical solutions.
The book then discusses Simulink and a number of more variable types of problems, including optimization, iterative methods
, partial differential equations, and LaPlace transforms.