Redimension des figure 6 et 7.

Arthur HUGEAT
1 parent 6f7c0de29f
Showing 3 changed files with 7 additions and 7 deletions Side-by-side Diff
ifcs2018_proceeding.tex
images/fir-mono-vs-fir-series-noise-fixe-mean-light.pdf
images/fir-mono-vs-fir-series-noise-fixe-median-light.pdf
@@ -119,7 +119,7 @@
 \begin{figure}[h!tb]
 \includegraphics[width=\linewidth]{images/demo_filtre}
 \caption{Impact of the quantization resolution of the coefficients: the quantization is
-set to 6~bits -- with the horizontal black lines indicating $\pm$1 least significant bit -- setting 
+set to 6~bits -- with the horizontal black lines indicating $\pm$1 least significant bit -- setting
 the 30~first and 30~last coefficients out of the initial 128~band-pass
 filter coefficients to 0 (red dots).}
 \label{float_vs_int}
@@ -187,7 +187,7 @@
 \begin{figure}[h!tb]
 \begin{center}
 \includegraphics[width=.5\linewidth]{schema2}
-\caption{Shape of the filter transmitted power $P$ as a function of frequency: 
+\caption{Shape of the filter transmitted power $P$ as a function of frequency:
 the bandpass BP is considered to occupy the initial
 40\% of the Nyquist frequency range, the stopband the last 40\%, allowing 20\% transition
 width.}
  
@@ -207,11 +207,11 @@
 To explain the system \ref{model-FIR}, $\mathcal{R}_i$ represents the rejection of depending on $N_i$ and $C_i$, $\mathcal{A}$
 is a theoretical area occupation of the processing block on the FPGA, and $\Delta_i$ is the total rejection for the current stage $i$.
 Since the function $\mathcal{F}$ cannot be explictly expressed, we run simulations to determine the rejection depending
-on $N_i$ and $C_i$. However, selecting the right filter requires a clear definition of the rejection criterion. Selecting an  
-incorrect criterion will lead the linear program solver to produce a solution which might not meet the user requirements. 
+on $N_i$ and $C_i$. However, selecting the right filter requires a clear definition of the rejection criterion. Selecting an
+incorrect criterion will lead the linear program solver to produce a solution which might not meet the user requirements.
 Hence, amongst various criteria including the mean or median value of the FIR response in the stopband as will
 be illustrated lated (section \ref{median}), we have designed
-a criterion aimed at avoiding ripples in the passband and considering the maximum of the FIR spectral response in the stopband 
+a criterion aimed at avoiding ripples in the passband and considering the maximum of the FIR spectral response in the stopband
 (Fig. \ref{rejection-shape}). The bandpass criterion is defined as the sum of the absolute values of the spectral response
 in the bandpass, reminiscent of a standard deviation of the spectral response: this criterion must be minimized to avoid
 ripples in the passband. The stopband transfer function maximum must also be minimized in order to improve the filter
@@ -329,7 +329,7 @@
 in these cases, are shown in Figs. \ref{compare-mean} and \ref{compare-median}.
  
 \begin{figure}[h!tb]
-\includegraphics[width=\linewidth]{images/fir-mono-vs-fir-series-noise-fixe-mean.pdf}
+\includegraphics[width=\linewidth]{images/fir-mono-vs-fir-series-noise-fixe-mean-light.pdf}
 \caption{Comparison of the rejection capability between a series of FIR and a monolithic FIR
 with a cutoff frequency set at half the Nyquist frequency.}
 \label{compare-mean}
@@ -347,7 +347,7 @@
 selected earlier (Fig. \ref{compare-fir}).
  
 \begin{figure}[h!tb]
-\includegraphics[width=\linewidth]{images/fir-mono-vs-fir-series-noise-fixe-median.pdf}
+\includegraphics[width=\linewidth]{images/fir-mono-vs-fir-series-noise-fixe-median-light.pdf}
 \caption{Comparison of the rejection capability between a series of FIR and a monolithic FIR
 with a cutoff frequency set at half the Nyquist frequency.}
 \label{compare-median}
...	...	@@ -119,7 +119,7 @@
119	119	\begin{figure}[h!tb]
120	120	\includegraphics[width=\linewidth]{images/demo_filtre}
121	121	\caption{Impact of the quantization resolution of the coefficients: the quantization is
122		-set to 6~bits -- with the horizontal black lines indicating $\pm$1 least significant bit -- setting
	122	+set to 6~bits -- with the horizontal black lines indicating $\pm$1 least significant bit -- setting
123	123	the 30~first and 30~last coefficients out of the initial 128~band-pass
124	124	filter coefficients to 0 (red dots).}
125	125	\label{float_vs_int}
...	...	@@ -187,7 +187,7 @@
187	187	\begin{figure}[h!tb]
188	188	\begin{center}
189	189	\includegraphics[width=.5\linewidth]{schema2}
190		-\caption{Shape of the filter transmitted power $P$ as a function of frequency:
	190	+\caption{Shape of the filter transmitted power $P$ as a function of frequency:
191	191	the bandpass BP is considered to occupy the initial
192	192	40\% of the Nyquist frequency range, the stopband the last 40\%, allowing 20\% transition
193	193	width.}
194	194
...	...	@@ -207,11 +207,11 @@
207	207	To explain the system \ref{model-FIR}, $\mathcal{R}_i$ represents the rejection of depending on $N_i$ and $C_i$, $\mathcal{A}$
208	208	is a theoretical area occupation of the processing block on the FPGA, and $\Delta_i$ is the total rejection for the current stage $i$.
209	209	Since the function $\mathcal{F}$ cannot be explictly expressed, we run simulations to determine the rejection depending
210		-on $N_i$ and $C_i$. However, selecting the right filter requires a clear definition of the rejection criterion. Selecting an
211		-incorrect criterion will lead the linear program solver to produce a solution which might not meet the user requirements.
	210	+on $N_i$ and $C_i$. However, selecting the right filter requires a clear definition of the rejection criterion. Selecting an
	211	+incorrect criterion will lead the linear program solver to produce a solution which might not meet the user requirements.
212	212	Hence, amongst various criteria including the mean or median value of the FIR response in the stopband as will
213	213	be illustrated lated (section \ref{median}), we have designed
214		-a criterion aimed at avoiding ripples in the passband and considering the maximum of the FIR spectral response in the stopband
	214	+a criterion aimed at avoiding ripples in the passband and considering the maximum of the FIR spectral response in the stopband
215	215	(Fig. \ref{rejection-shape}). The bandpass criterion is defined as the sum of the absolute values of the spectral response
216	216	in the bandpass, reminiscent of a standard deviation of the spectral response: this criterion must be minimized to avoid
217	217	ripples in the passband. The stopband transfer function maximum must also be minimized in order to improve the filter
...	...	@@ -329,7 +329,7 @@
329	329	in these cases, are shown in Figs. \ref{compare-mean} and \ref{compare-median}.
330	330
331	331	\begin{figure}[h!tb]
332		-\includegraphics[width=\linewidth]{images/fir-mono-vs-fir-series-noise-fixe-mean.pdf}
	332	+\includegraphics[width=\linewidth]{images/fir-mono-vs-fir-series-noise-fixe-mean-light.pdf}
333	333	\caption{Comparison of the rejection capability between a series of FIR and a monolithic FIR
334	334	with a cutoff frequency set at half the Nyquist frequency.}
335	335	\label{compare-mean}
...	...	@@ -347,7 +347,7 @@
347	347	selected earlier (Fig. \ref{compare-fir}).
348	348
349	349	\begin{figure}[h!tb]
350		-\includegraphics[width=\linewidth]{images/fir-mono-vs-fir-series-noise-fixe-median.pdf}
	350	+\includegraphics[width=\linewidth]{images/fir-mono-vs-fir-series-noise-fixe-median-light.pdf}
351	351	\caption{Comparison of the rejection capability between a series of FIR and a monolithic FIR
352	352	with a cutoff frequency set at half the Nyquist frequency.}
353	353	\label{compare-median}