Coming soon.
1Question 1¶
1.1Solution¶
1.1.1Part (a)¶
State the fixed point theorem
ez
1.1.2Part (b)¶
Find an interval and starting point on which some iterative scheme for finding something satisfies the conditions of the theorem, and find the rate of convergence.
Choose an interval that satisfies the FPT. Rate of convergence is probably linear cus the first deriv is non-zero
1.1.3Part (c)¶
Aitken's method.
Hopefully it's not on our syllabus because I'm not going to cover it.
1.2Accuracy and discussion¶
2Question 2¶
2.1Solution¶
2.1.1Part (a)¶
Define fundamental Lagrange polys
See the HTSEFP
2.1.2Part (b)¶
Show uniqueness
See the HTSEFP
2.1.3Part (c)¶
Find the interpolating poly
Construct the table of divided differences (remember to DIVIDE ... DIVIDED differences)
$f[x_i]$ | $f[x_{i-1}, x_i]$ | $f[x_{i-2}, x_{i-1}, x_i]$ | $f[x_{i-3}, x_{i-2}, x_{i-1}, x]$ | |
---|---|---|---|---|
$x_0 = 0$ | 0 | |||
$x_1 = 1$ | 0 | 0 | ||
$x_2 = 2$ | 4 | 4 | 2 | |
$x_3 = 3$ | 6 | 2 | -1 | -1 |
$$p_3(x) = 0 + 0(x -0) + 2(x-0)(x-1) -1(x-0)(x-1)(x-2) = 2x(x-1) - x(x-1)(x-2)$$
Find the error bounds
Use the given formula. Should get $10/24 * (2.5-0)(2.5-1)(2.5-2)(2.5-3)$ so the error $\leq 0.390625$
2.2Accuracy and discussion¶
No solutions for this that I can find. Not sure if right
3Question 3¶
3.1Solution¶
3.1.1Part (a)¶
Diff between Lagrange/Hermite? Clamped/natural cubic spline?
see htsefp
3.1.2Part (b)¶
Find constants for some natural cubic spline
see htsefp
3.1.3Part (c)¶
Bezier curve
same as 2009 q3 (c)
3.2Accuracy and discussion¶
4Question 4¶
4.1Solution¶
4.1.1Part (a)¶
Use quadratic formula to approximate roots
idk, just use it, not really worth thinking about
4.1.2Part (b)¶
Use centred-difference expression for approximating second derivative
basically the same as 2009
4.2Accuracy and discussion¶
5Question 5¶
5.1Solution¶
5.1.1Part (a)¶
Define deg of acc for quadrature
see htsefp
5.1.2Part (b)¶
Find constants to maximise deg of acc
see htsefp
5.1.3Part (c)¶
Find deg of acc for previous method, and find the constant $k$
see htsefp
5.2Accuracy and discussion¶
6Question 6¶
6.1Solution¶
6.1.1Part (a)¶
Use composite trapezoidal rule to approximate something
see htsefp
6.1.2Part (b)¶
Derive error bound
see htsefp
6.1.3Part (c)¶
Obtain upper bounds for error for previous approximation
First, compute the second derivative:
$$f'(x) = 2xe^{x^2} \quad f''(x) = 2e^{x^2} + 4x^2e^{x^2} = 2e^{x^2}(1+2x^2)$$
Clearly $f''$ is a non-decreasing function for the interval $[0, 1]$. So the maximum $f''$-value is when $x = 1$, at which point $f''(1) = 2e(1+2) = 6e$.
For $h=0.25$:
$$I(f) - I_h(f) \leq -\frac{1-0}{12}(0.25)^2 \max_{\xi \in [0, 1]} f''(\xi) = -\frac{6e}{192} \approx -0.084946$$
For $h=0.5$
$$I(f) - I_h(f) \leq -\frac{1-0}{12}(0.5)^2 \max_{\xi \in [0, 1]} f''(\xi) = -\frac{6e}{48} \approx -0.0212365$$
6.1.4Part (d)¶
Apply one step of Richardson extrap
if this shows up on the final im just gonna wing it
6.2Accuracy and discussion¶
7Question 7¶
Runge-Kutta
7.1Solution¶
7.1.1Part (a)¶
Define local truncation error, find order of method
see htsefp
7.1.2Part (b) (i)¶
Show some identity for $w_{i+1}$
see htsefp
7.1.3Part (b) (ii)¶
What conditions on $h$ are required to get the limit of $w_i = 0$ as $i \to \infty$
see htsefp
7.2Accuracy and discussion¶
8Question 8¶
Linear shooting stuff, not gonna bother