[Analysis] Various fixes and optimizations

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2026-02-01 15:31:56 +01:00
parent 09b635ebf0
commit 19ce8d3af8
4 changed files with 16 additions and 4 deletions

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@@ -16,11 +16,18 @@ The homogeneous equation will then be all the elements of the set summed up.\\
\shade{gray}{Inhomogeneous Equation}\rmvspace
\begin{enumerate}[noitemsep]
\item \bi{(Case 1)} $b(x) = c x^d e^{\alpha x}$, with special cases $x^d$ and $e^{\alpha x}$:
$f_p = Q(x) e^{\alpha x}$ with $Q$ a polynomial with $\deg(Q) \leq j + d$, where $j$ is multiplicity of root $\alpha$ (if $P(\alpha) \neq 0$, then $j = 0$) of characteristic polynomial
$f_p = Q(x) e^{\alpha x}$ with $Q$ a polynomial with $\deg(Q) \leq j + d$,
where $j$ is multiplicity of root $\alpha$ (if $P(\alpha) \neq 0$, then $j = 0$) of characteristic polynomial
\item \bi{(Case 2)} $b(x) = c x^d \cos(\alpha x)$, or $b(x) = c x^d \sin(\alpha x)$:
$f_p = Q_1(x) \cdot \cos(\alpha x) + Q_2(x9 \cdot \sin(\alpha x))$,
where $Q_i(x)$ a polynomial with $\deg(Q_i) \leq d + j$, where $j$ is the multiplicity of root $\alpha i$ (if $P(\alpha i) \neq 0$, then $j = 0$) of characteristic polynomial
$f_p = Q_1(x) \cdot \cos(\alpha x) + Q_2(x) \cdot \sin(\alpha x))$,
where $Q_i(x)$ a polynomial with $\deg(Q_i) \leq d + j$,
where $j$ is the multiplicity of root $\alpha i$ (if $P(\alpha i) \neq 0$, then $j = 0$) of characteristic polynomial
\item \bi{(Case 3)} $b(x) = c e^{\alpha x} \cos(\beta x)$, or $b(x) = c e^{\alpha x} \sin(\beta x)$, use the Ansatz
$Q_1(x) e^{\alpha x} \sin(\beta x) + Q_2(x) e^{\alpha x} \cos(\beta x)$, agasin with the same polynomial.
Often, it is sufficent to have a polynomial of degree 0 (i.e. constant)
\end{enumerate}
For inhomogeneous parts with addition or subtraction, the above cases can be combined.
For any cases not covered, start with the same form as the inhomogeneous part has (for trigonometric functions, duplicate it with both $\sin$ and $\cos$).
\rmvspace\shade{gray}{Other methods}\rmvspace
\begin{itemize}[noitemsep]

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@@ -16,9 +16,10 @@
We usually call $f : X \rightarrow \R^n$ (or sometimes $V$ a \bi{vector field}, which maps each point $x \in X$ to a vector in $\R^n$, displayed as originating from $x$.
Ideally, to compute a line integral, we compute the derivative of $\gamma$ separately ($\gamma(t) = s$ usually, derive component-wise),
limits of integration are start and end of section.
\hl{Be careful with hat functions} like $|x|$, we need two separate integrals for each side of the center!
\hl{Be careful with hat functions} like $|x|$, we need two separate integrals for each side of the center!\\
Alternatively, see section \ref{sec:green-formula} for a faster way.
For calculating the area enclosed by the curve, see there too.
\bi{For computing}, we usually use the first integral in def \ref{all:4-1-1} (3).
\setLabelNumber{all}{4}
\compactdef{Oriented reparametrization} of $\gamma$ is parametrized curve $\sigma : [c, d] \rightarrow \R^n$ s.t $\sigma = \gamma \circ \varphi$, with $\varphi : [c, d] \rightarrow I$ cont. map,

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@@ -61,3 +61,7 @@ The center of mass of an object $\cU$ is given by $\displaystyle \overline{x}_i
\rmvspace
\shade{gray}{Dot product} For vectors $v, w \in \R^n$, we have $\displaystyle v \cdot w = \sum_{i = 1}^{n} v_i \cdot w_i$
\rmvspace
\shade{gray}{Matrix-Vector product} Given vector $v\in \R^m$ and matrix $A \in \R^{n \times m}$,
we have $A \cdot v = u$ where $ \displaystyle u_j = \sum_{i = 1}^{m} v_i \cdot A_{j, i}$.