The idea of fixed-point iterations can be seen from
Newton's formula. In the context of computing roots of equations, Newton's
method can be viewed as a fixed-point iteration by viewing
.
The fixed-point iteration framework allows for greater
freedom in formulation of iteration schemes and provides a more rigorous
framework for the analysis of convergence. The following theorem presents
the idea of consistency. That is, if the sequence
converges, then it necessarily converges to a fixed point.
The analysis of convergence of the fixed point iterations also produces additional information that can be used to examine the rate of convergence and a mechanism to detect convergence to within a certain amount of accuracy. The discussion of convergence for fixed-point iterations begins with a lemma which permits the existence of a fixed point.
Proof:
where $, $ using the Mean-Value theorem, Theorem 1.5. Taking absolute values,
Since $< 1$ by the statement of the theorem $1-> 0$. This implies $|-|=0$, or $= $ which establishes uniqueness.
Note that
where $c_n-1 , x_n-1 .$ Taking absolute values yields
Since $< 1$, $e_n 0$ and hence $x_n $.
or
Thus, $|-x_0| 11-|x_1-x_0|$. This, in combination with Equation 4.16 completes the proof.
for some $c_n , x_n+1$. Since $x_n+1 $ it follows that $c_n $. Using the continuity assumption on $g'(x)$, we have
Thus, for $x_n$ sufficiently close to $$,