ece204: add derivatives

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eggy 2023-11-07 13:51:46 -05:00
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@ -84,3 +84,91 @@ $$\boxed{f(x)=b_0+b_1(x-x_0)+b_2(x-x_0)(x-x_1)}$$
$$ $$
b_2=\frac{\frac{f(x_2)-f(x_1)}{x_2-x_1}-\frac{f(x_1)-f(x_0)}{x_1-x_0}}{x_2-x_0} b_2=\frac{\frac{f(x_2)-f(x_1)}{x_2-x_1}-\frac{f(x_1)-f(x_0)}{x_1-x_0}}{x_2-x_0}
$$ $$
## Derivatives
Derivatives are estimated based on first principles:
$$f'(x)=\frac{f(x+h)-f(x)}{h}$$
### Derivatives of continuous functions
At a desired $x$ for $f'(x)$:
1. Choose an arbitrary $h$
2. Calculate derivative via first principles
3. Shrink $h$ and recalculate derivative
4. If the answer is drastically different, repeat step 3
### Derivatives of discrete functions
Guesses are made based on the average slope between two points.
$$f'(x_i)=\frac{f(x_{i+1})-f(x_i)}{x_{i+1}-x_i}$$
### Divided differences
- Using the next term, or a $\Delta x > 0$ indicates a **forward divided difference (FDD)**.
- Using the previous term, or a $\Delta x < 0$ indicates a **backward divided difference (BDD)**.
The **central divided difference** averages both if $h$ or $\Delta x$ of the forward and backward DDs are equal.
$$f'(x)=CDD=\frac{f(x+h)-f(x-h)}{2h}$$
### Higher order derivatives
Taking the Taylor expansion of the function or discrete set and then expanding it as necessary can return any order of derivative. This also applies for $x-h$ if positive and negative are alternated.
$$f(x+h)=f(x)+f'(x)h+\frac{f''(x)}{2!}h^2+\frac{f'''(x)}{3!}h^3$$
!!! example
To find second order derivatives:
\begin{align*}
f''(x)&=\frac{2f(x+h)-2f(x)-2f'(x)h}{h^2} \\
&=\frac{2f(x+h)-2f(x)-(f(x+h)-f(x-h))}{h^2} \\
&=\frac{f(x+h)-2f(x)+f(x-h)}{h^2}
\end{align*}
!!! example
$f''(3)$ if $f(x)=2e^{1.5x}$ and $h=0.1$:
\begin{align*}
f''(3)&=\frac{f(3.1)-2\times2f(3)+f(2.9)}{0.1^2} \\
&=405.08
\end{align*}
For discrete data:
- If the desired point does not exist, differentiating the surrounding points to create a polynomial interpolation of the derivative may be close enough.
!!! example
| t | 0 | 10 | 15 | 20 | 22.5 | 30 |
| --- | --- | --- | --- | --- | --- | --- |
| v(t) | 0 | 227.04 | 362.78 | 517.35 | 602.47 | 901.67 |
$v'(16)$ with FDD:
Using points $t=15,t=20$:
\begin{align*}
v'(x)&=\frac{f(x+h)-f(x)}{h} \\
&=\frac{f(15+5)-f(15)}{5} \\
&=\frac{517.35-362.78}{5} \\
&=30.914
\end{align*}
$v'(16)$ with Newton's first-order interpolation:
\begin{align*}
v(t)&=v(15)+\frac{v(20)-v(15)}{20-15}(t-15) \\
&=362.78+30.914(t-15) \\
&=-100.93+30.914t \\
v'(t)&=\frac{v(t+h)-v(t)}{2h} \\
&=\frac{v(16.1)-v(15.9)}{0.2} \\
&=30.914
\end{align*}
- If the spacing is not equal (to make DD impossible), again creating an interpolation may be close enough.
- If data is noisy, regressing and then solving reduces random error.