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Merge pull request #4 from f-cazzola/master
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fix typo
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edomora97 authored Jun 8, 2020
2 parents a0efd55 + 86b9f7e commit 5c069bf
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2 changes: 1 addition & 1 deletion lectures/2020-04-30.tex
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Expand Up @@ -26,7 +26,7 @@

The performance index can be redefined:
\[
\tilde{J}_H (\theta) = \frac{1}{H} \sum_{i=1}^H \gamma_i \left(W(e^{j\omega_i};\theta) - \frac{\hat{B}_i}{A_i}e^{j\hat{\phi_i}}\right)^2
\tilde{J}_H (\theta) = \frac{1}{H} \sum_{i=1}^H \lambda_i \left(W(e^{j\omega_i};\theta) - \frac{\hat{B}_i}{A_i}e^{j\hat{\phi_i}}\right)^2
\]

Another \emph{trick}: more dense $\omega_i$ spacing in the frequency region of special interest (not really used).
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2 changes: 1 addition & 1 deletion lectures/2020-05-05.tex
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Expand Up @@ -132,7 +132,7 @@ \subsection{Exogenous input}
\end{tikzpicture}
\end{figure}

Notice that $K(t)$ remains the same because $P(t)$ is the covariance of the prediction error on $x(t)$ and remains the same because $Gu(t)$ introduce any additional noise or uncertainties to the system.
Notice that $K(t)$ remains the same because $P(t)$ is the covariance of the prediction error on $x(t)$ and remains the same because $Gu(t)$ doesn't introduce any additional noise or uncertainties to the system.
$Gu(t)$ is a totally known (deterministic) signal.

\subsection{Multi-step Prediction}
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4 changes: 2 additions & 2 deletions lectures/2020-05-14.tex
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Expand Up @@ -100,7 +100,7 @@ \section{Non-linear Systems}
\begin{figure}[H]
\centering
\begin{tikzpicture}[node distance=2cm,auto,>=latex']
\node[int,double border,align=center] at (0,0) (n) {non-lin\\dyn T.I. sys};
\node[int,dashed border,align=center] at (0,0) (n) {non-lin\\dyn T.I. sys};
\draw[<-,transform canvas={yshift=0.3cm}] (n) -- ++(-2,0) node[left] {$u(t)$};
\draw[<-,transform canvas={yshift=-0.3cm}] (n) -- ++(-2,0) node[left] {$y(t)$};
\draw[->] (n) -- ++(2,0) node[right] {$\hat{x}(t)$};
Expand Down Expand Up @@ -308,7 +308,7 @@ \section{Non-linear Systems}
\begin{figure}[H]
\centering
\begin{tikzpicture}[node distance=2cm,auto,>=latex']
\node[int, dashed border, minimum width=1.5cm, minimum height=3cm] at (0,0) (sys) {};
\node[int, double border, minimum width=1.5cm, minimum height=3cm] at (0,0) (sys) {};
\node[int, dashed border, minimum height=3cm] at (4,0) (f) {$f(\cdot,\theta)$};

\draw[<-,transform canvas={yshift=0.5cm}] (sys) -- ++(-2cm,0) node[left] {$u(t)$};
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