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Root-Finding Check

  • Root exists in [a,b][a,b] if f(x)f(x) is continuous on [a,b][a,b] and f(a)f(b)<0f(a)f(b)<0.
  • Linear eqn: highest power of variable is 11.
  • Nonlinear eqn: power >1>1 or curve-type relation.

Graphical Method

  • Plot y=f(x)y=f(x).
  • Root = point where graph cuts xx-axis.
  • For x32x5=0x^3-2x-5=0 sign changes: f(2)=1,f(3)=16f(2)=-1,\quad f(3)=16 and f(2.09)0.0507,f(2.10)0.061f(2.09)\approx -0.0507,\quad f(2.10)\approx 0.061
  • Approx root: x2.09x\approx 2.09

Bisection Method

Conditions:

  • Continuous function
  • Opposite signs at endpoints

Formula:

c=a+b2c=\frac{a+b}{2}

Rule:

  • If f(a)f(c)<0f(a)f(c)<0, new interval [a,c][a,c]
  • Otherwise new interval [c,b][c,b]

Stopping:

ba2<TOL\frac{b-a}{2}<\mathrm{TOL}

Exam result:

x37=0x1.910x^3-7=0 \Rightarrow x\approx 1.910

Fixed Point Iteration

Write

x=g(x)x=g(x)

Iteration:

xn+1=g(xn)x_{n+1}=g(x_n)

Good exam form:

x=6x3x=\sqrt[3]{6-x}

For

x3+x6=0x^3+x-6=0

with x0=1.5x_0=1.5:

x1.6346x\approx 1.6346

Secant Method

Formula:

xn+1=xnf(xn)(xnxn1)f(xn)f(xn1)x_{n+1}=x_n-\frac{f(x_n)(x_n-x_{n-1})}{f(x_n)-f(x_{n-1})}

No derivative needed.

For

x34x9=0x^3-4x-9=0

use

x0=2,x1=3x_0=2,\quad x_1=3

After 5 iterations:

x2.706528x\approx 2.706528

Newton-Raphson Method

Formula:

xn+1=xnf(xn)f(xn)x_{n+1}=x_n-\frac{f(x_n)}{f'(x_n)}

Stopping:

xn+1xn<εorf(xn+1)<ε|x_{n+1}-x_n|<\varepsilon \quad \text{or} \quad |f(x_{n+1})|<\varepsilon

For

f(x)=x32x2+3f(x)=x^3-2x^2+3 f(x)=3x24xf'(x)=3x^2-4x

Iteration form:

xn+1=xnxn32xn2+33xn24xnx_{n+1}=x_n-\frac{x_n^3-2x_n^2+3}{3x_n^2-4x_n}

With x0=1.5x_0=-1.5:

x1x\approx -1

Gaussian Elimination

Steps:

  1. Write augmented matrix.
  2. Make zeros below pivots.
  3. Convert to upper triangular form.
  4. Use back substitution.

Exam result for

3x+yz=42x4y+5z=3x+2y+3z=10\begin{aligned} 3x+y-z&=4\\ 2x-4y+5z&=-3\\ x+2y+3z&=10 \end{aligned} x=0.84,y=2.72,z=1.24x=0.84,\quad y=2.72,\quad z=1.24

Partial Pivoting

Use when pivot is zero or very small.

Why:

  • avoids division by tiny number
  • reduces round-off error
  • improves stability

Exam trigger:

  • first pivot 0.20.2 too small, so swap rows first

Exam result:

x0.8491,y4.6415,z5.7547x\approx -0.8491,\quad y\approx 4.6415,\quad z\approx -5.7547

Gauss-Seidel Method

Use when:

  • system is diagonally dominant
  • iterative approx acceptable

Rearrange each equation:

x=11y+z10,y=122xz10,z=14+2x3y10x=\frac{11-y+z}{10},\qquad y=\frac{12-2x-z}{10},\qquad z=\frac{14+2x-3y}{10}

Diagonal dominance check:

10>2,10>3,10>5|10|>2,\quad |10|>3,\quad |10|>5

Start with

x0=y0=z0=0x_0=y_0=z_0=0

After 4 iterations:

x1.15493,y0.83090,z1.38172x\approx 1.15493,\quad y\approx 0.83090,\quad z\approx 1.38172

Exam Hit List

  • Sign-change test
  • Bisection interval update
  • Fixed-point form choice
  • Secant formula
  • Newton-Raphson derivative + iteration
  • Augmented matrix
  • Upper triangular form
  • Partial pivoting row swap
  • Diagonal dominance test
  • Gauss-Seidel iteration table

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