Nonlinear Equations - UFRJ
Nonlinear Equations - UFRJ
Nonlinear Equations - UFRJ
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[SEC. 9.4: THE ALPHA THEOREM 131<br />
Those will be compared to<br />
ˆβ i = β(h βγ , t i )) and ˆγ i = γ(h βγ , t i )).<br />
Induction hypothesis: β i ≤ ˆβ i and for all l ≥ 2,<br />
‖Df(X i ) † D l f(X i )‖ ≤ − h(l) βγ (t i)<br />
h ′ βγ (t i) .<br />
The initial case when i = 0 holds by construction.<br />
assume that the hypothesis holds for i. We will estimate<br />
So let us<br />
β i+1 ≤ ‖Df(X i+1 ) † Df(X i )‖‖Df(X i ) † f(X i+1 )‖ (9.4)<br />
and<br />
γ i+1 ≤ ‖Df(X i+1 ) † Df(X i )‖ ‖Df(X i) † D k f(X i+1 )‖<br />
. (9.5)<br />
k!<br />
By construction, f(X i ) + Df(X i )(X i+1 − X i ) = 0. The Taylor<br />
expansion of f at X i is therefore<br />
Df(X i ) † f(X i+1 ) = ∑ k≥2<br />
Passing to norms,<br />
while we know from (7.14) that<br />
ˆβ i+1 = − h βγ(t i+1 )<br />
h ′ βγ (t i)<br />
From Lemma 9.4,<br />
Df(X i ) † D k f(X i )(X i+1 − X i ) k<br />
k!<br />
‖Df(X i ) † f(X i+1 )‖ ≤ β2 i γ i<br />
1 − γ i<br />
= β(h βγ, t i ) 2 γ(h βγ , t i )<br />
1 − γ(h βγ , t i )<br />
‖Df(X i+1 ) † Df(X i )‖ ≤ (1 − β iγ i ) 2<br />
.<br />
ψ(β i γ i )<br />
= ˆβ 2 i ˆγ i<br />
1 − ˆγ i