Obisidian vault auto-backup: 02-12-2024 09:07:09 on constellation. 1 files edited

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@@ -107,6 +107,119 @@ $$\nabla \times f = \frac{\partial f_y}{\partial x} - \frac{\partial f_x}{\parti
## Théorème de Schwarz
$$\frac{\partial^2 f}{\partial x \partial y} = \frac{\partial^2 f}{\partial y \partial x}, \quad \text{si } f_{xy} \text{ et } f_{yx} \text{ sont continues.}$$
$$
\documentclass{article}
\usepackage{amsmath, tikz}
\usepackage{pgfplots}
\pgfplotsset{compat=1.17}
\section*{Convolution : Exemple avec \(f(t)\) et \(g(t)\)}
\subsection*{Les fonctions}
1. \(f(t)\), définie comme :
\[
f(t) =
\begin{cases}
e^t & \text{si } t \leq 0, \\
e^{-t} & \text{si } t > 0.
\end{cases}
\]
2. \(g(t)\), définie comme :
\[
g(t) =
\begin{cases}
1 & \text{si } 0 \leq t \leq 1, \\
0 & \text{sinon.}
\end{cases}
\]
\subsection*{Définition de la convolution}
La convolution est donnée par :
\[
(f * g)(t) = \int_{-\infty}^{\infty} f(\tau) g(t - \tau) \, d\tau
\]
Pour ce cas spécifique :
\[
(f * g)(t) =
\begin{cases}
\int_{0}^{t} e^\tau \, d\tau & \text{si } t \leq 1, \\
\int_{t-1}^{t} e^\tau \, d\tau & \text{si } t > 1.
\end{cases}
\]
\subsection*{Résultat de la convolution}
Calculons les deux cas :
1. Si \(t \leq 1\) :
\[
(f * g)(t) = \int_{0}^{t} e^\tau \, d\tau = \left[e^\tau \right]_{0}^{t} = e^t - 1.
\]
2. Si \(t > 1\) :
\[
(f * g)(t) = \int_{t-1}^{t} e^\tau \, d\tau = \left[e^\tau \right]_{t-1}^{t} = e^t - e^{t-1}.
\]
\subsection*{Visualisation des fonctions et de la convolution}
\begin{figure}[ht]
\centering
\begin{tikzpicture}
% Graph for f(t)
\begin{axis}[
width=12cm,
height=6cm,
xlabel={$t$},
ylabel={$f(t)$ and $g(t)$},
axis x line=middle,
axis y line=middle,
ymin=0, ymax=2,
xmin=-2, xmax=2,
samples=100,
legend style={at={(1.1,1)},anchor=north west}
]
% f(t)
\addplot[domain=-2:0, thick, blue] {exp(x)} node[pos=0.5, above] {};
\addplot[domain=0:2, thick, blue] {exp(-x)} node[pos=0.5, above] {};
\addlegendentry{$f(t)$}
% g(t)
\addplot[domain=0:1, thick, red] {1} node[pos=0.5, above] {};
\addplot[domain=-2:0, thick, red] {0};
\addplot[domain=1:2, thick, red] {0};
\addlegendentry{$g(t)$}
\end{axis}
\end{tikzpicture}
\caption{Les fonctions \(f(t)\) et \(g(t)\).}
\end{figure}
\begin{figure}[ht]
\centering
\begin{tikzpicture}
% Graph for the convolution
\begin{axis}[
width=12cm,
height=6cm,
xlabel={$t$},
ylabel={$(f * g)(t)$},
axis x line=middle,
axis y line=middle,
ymin=0, ymax=2,
xmin=-1, xmax=3,
samples=100
]
% Convolution result
\addplot[domain=0:1, thick, green] {exp(x) - 1};
\addplot[domain=1:3, thick, green] {exp(x) - exp(x-1)};
\end{axis}
\end{tikzpicture}
\caption{Résultat de la convolution : \((f * g)(t)\).}
\end{figure}
\end{document}
$$
---
© Félix MARQUET