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However the downside of forming the normal equations is that the condition number κ(A T A) is equal to κ 2 (A) and so the rate of convergence of CGNR may be slow and the quality of the approximate solution may be sensitive to roundoff errors. Finding a good preconditioner is often an important part of using the CGNR method.
In asymptotic analysis in general, one sequence () that converges to a limit is said to asymptotically converge to with a faster order of convergence than another sequence () that converges to in a shared metric space with distance metric | |, such as the real numbers or complex numbers with the ordinary absolute difference metrics, if
where is a scalar parameter that has to be chosen such that the sequence () converges. It is easy to see that the method has the correct fixed points , because if it converges, then x ( k + 1 ) ≈ x ( k ) {\displaystyle x^{(k+1)}\approx x^{(k)}} and x ( k ) {\displaystyle x^{(k)}} has to approximate a solution of A x = b {\displaystyle Ax=b} .
If an equation can be put into the form f(x) = x, and a solution x is an attractive fixed point of the function f, then one may begin with a point x 1 in the basin of attraction of x, and let x n+1 = f(x n) for n ≥ 1, and the sequence {x n} n ≥ 1 will converge to the solution x.
In numerical analysis, Richardson extrapolation is a sequence acceleration method used to improve the rate of convergence of a sequence of estimates of some value = (). In essence, given the value of A ( h ) {\displaystyle A(h)} for several values of h {\displaystyle h} , we can estimate A ∗ {\displaystyle A^{\ast }} by extrapolating the ...
Although the convergence of x n + 1 − x n in this case is not very rapid, it can be proved from the iteration formula. This example highlights the possibility that a stopping criterion for Newton's method based only on the smallness of x n + 1 − x n and f ( x n ) might falsely identify a root.
In numerical analysis, fixed-point iteration is a method of computing fixed points of a function.. More specifically, given a function defined on the real numbers with real values and given a point in the domain of , the fixed-point iteration is + = (), =,,, … which gives rise to the sequence,,, … of iterated function applications , (), (()), … which is hoped to converge to a point .
Given a function :, consider the problem of finding a fixed point of , which is a solution to the equation () =.A classical approach to the problem is to employ a fixed-point iteration scheme; [2] that is, given an initial guess for the solution, to compute the sequence + = until some convergence criterion is met.