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Applied Numerical Analysis PowerPoint Presentation

Applied Numerical Analysis

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### Applied Numerical Analysis

Chapter 2 Notes (continued)

Order of Convergence of a SequenceAsymptotic Error Constant (Defs)

- Suppose is a sequence that converges to p, with pn p for all n. If positive constants and exist with
then converges to p of order with asymptotic error constant .

- If =1, linear convergence.
- If = 2, quadratic convergence.

Test for Linear Convergence (Thm 2.7)

- Let g C[a,b] be such that g(x) [a,b], for all x [a,b]. Suppose in addition that g’ is continuous on (a,b) and a positive constant k <1 exists with
|g’(x)| < k, for all x (a,b).

If g’(p) 0, then for any number p0 in [a,b], the sequence pn = g(pn-1), for n 1, converges only linearly to the unique fixed point p in [a,b].

Test for Quadratic Convergence (Thm 2.8)

Let p be a solution for the equation x = g(x). Suppose that g’(p) = 0 and g” is contin-uous and strictly bounded by M on an open interval I containing p. Then there exists a > 0 such that, for p0 [p - , p + ], the sequence defined by pn = g(pn-1), when

n 1, converges at least quadratically to p. Moreover, for sufficiently large values of n,

Solution of multiplicity zero. (Def 2.9)

- A solution p of f(x) = 0 is a zero of multiplicity m of f if for x p, we can write:
f(x) = (x – p)m q(x), where q(x) 0.

Functions with zeros of multiplicity m (Thms2.10,11)

f C1[a,b]has a simple zero at p in (a,b) if and only if f(p) = 0 but f’(p) 0.

The function f Cm[a,b] has a zero of multiplicity m at p in (a,b) if and only if

0 = f(p) = f’(p) =f”(p) = ... = f(m-1)(p) but f(m)(p) 0.

Aitken’s 2 Method Assumption

- Suppose is a linearly covergent sequence with limit p. If we can assume for n “suf-
- ficiently large” then by algebra:
and the sequence converges “more rapidly” than does .

Forward Difference (Def 2.12)

- For a given sequence , the forward difference pn, is defined by:
pn = pn+1 – pn, for n 0.

- So:
can be written:

“Converges more rapidly” (Thm 2.13)

- Suppose that is a sequence that converges linearly to the limit p and that for all sufficiently large values of n we have (pn– p)(pn+1– p) > 0. Then
the sequence converges to p

faster than in the sense that

Steffensen’s Method

- Application of Aitken’s 2 Method
- To find the solution of p = g(p) with initial approximation po.
- Find p1 = g(po) & p2 = g(p1)
- Then form interation:
- Use successive values for p0, p1, p2,.

Steffenson’s Theorem (Thm2.14)

- Suppose tht x = g(x) has the solution p with g’(p) 1. If there exists a > 0 such that g C3[p-,p+], then Steffenson’s method gives quadratic convergence for an p0 [p-,p+].

Fundamental Theorem of Algebra (Thm:2.15)

- If P(x) is a polynomial of degree n 1 with real or complex coefficients, then P(x) = 0 has a least one (possibly complex) root.
- If P(x) is a polynomial of degree n 1 with real or complex coefficients, then there exist unique constants x1,x2, ... xk, possibly complex, and unique positive integers m1, m2..., mk such that

Remainder and Factor Theorems:

- Remainder Theorem:
- If P(x) is divided by x-a, then the remainder upon dividing is P(a).

- Factor Theorem:
- If R(a) = 0, the x-a is a factor of P(x).

Rational Root Theorem:

- If P(x)=
and all ai Q, i=0n, (Q-the set of rational numbers)

then if P(x) has rational roots of the form p/q (in lowest terms),

a0 = k·p and an = c ·q with k and c elements of (-the set of integers)

Descartes’ Rule of Signs:

- The number of positive real roots of P(x) = 0, where P(x) is a polynomial with real coefficients, is eual to the number of variations in sign occurring in P(x), or else is less than this number by a positive even integer.
- Then number of negative real roots can by found by using the same rule on P(-x).

Horner’s Method (Synthetic Division)

- Example:
- 2|1 0 –9 4 12
|_ +2(1) +2(2) +2(-5) +2(-6)

1 2 -5 -6 | 0 = R

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