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authorFreeArtMan <dos21h@gmail.com>2017-07-17 22:45:53 +0100
committerFreeArtMan <dos21h@gmail.com>2017-07-17 22:45:53 +0100
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parent286256b66b36592073da3669520cc9022022aedb (diff)
downloadmd-content-d8b6557dc83e3739bf6c5bd47a037e70f0fc97ad.tar.gz
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More spell checking stuff
Diffstat (limited to 'md/writeup')
-rw-r--r--md/writeup/dsp_lp_filter.md10
1 files changed, 5 insertions, 5 deletions
diff --git a/md/writeup/dsp_lp_filter.md b/md/writeup/dsp_lp_filter.md
index 453f263..270fa4a 100644
--- a/md/writeup/dsp_lp_filter.md
+++ b/md/writeup/dsp_lp_filter.md
@@ -11,7 +11,7 @@ So what is low-pass filter? In DSP its algo that can filter some array of values
If you have recording sound were you noticed that flying mosquito is recorded then with is you can reduce noise from mosquito in recorded sound.
-If you just use filtr as a function then main params is how good are your filter and cutoff frequency. Good filter have higher number of filter coefficients with are determined from filter order. Cutoff frequency is set to normalised valueshtml from 0.0 ... 1.0. Set them according which part should be filtered.
+If you just use filter as a function then main params is how good are your filter and cut-off frequency. Good filter have higher number of filter coefficients with are determined from filter order. Cut-off frequency is set to normalised values html from 0.0 ... 1.0. Set them according which part should be filtered.
## Octave examples
@@ -43,7 +43,7 @@ Second picture showing phase response. Well for now it's not so "important".
Let's create some signal from couple of frequencies, like
100,400,750,1000,1200,1500 then let's do FFT to see what we have.
-![source signal](/img/dsp_lp_filter/signal_pre.png)
+![source signal](/img/dsp_lp_filter/signal_pre.png)Low FIR pass-filer
![source signal fft](/img/dsp_lp_filter/signal_pre_fft.png)
@@ -70,7 +70,7 @@ xlabel('Frequency (Hz)')
ylabel('Power/Frequency (dB/Hz)')
```
-Lets filter out with cutoff frequency 1000kHz. Should get rid of
+Lets filter out with cut-off frequency 1000kHz. Should get rid of
1000,1200,1500 frequencies in resulting FFT.
![output signal](/img/dsp_lp_filter/signal_post.png)
@@ -109,7 +109,7 @@ freqz(fir1(41,0.5));
Octave allows to see what filter properties is, also can choose appropriate filter type. Find how precise filter should be. And also test data on some signal sample. Now lets implement that with C.
-__Define FIR filter coeficients__
+__Define FIR filter coefficients__
```c
#define FIR_SIZE 12
@@ -251,7 +251,7 @@ int main(int argc, char **argv)
}
```
-## Using programm
+## Using program
```
./lpf1 1.0 0.0 0.0 0.0 0.0