First how to discretize the filter and signal by specific discretization amount and then apply the filter on...
I want to know if I have the first-order Chebyshev filter response as below:
H_filter(s) = 1/(-1-s) = real_H_filter (s) + j Imag_H_filter(s)
and also I have my signal as below:
G(s)= Gr (s) + j Gi (s)
How can I discretize the signal and filter by frequency rate of for example 0.0001 rad/s
and then apply the filter to signal to get the filtered signal in Python?
The filtered signal should be looked like below which can easily be decomposed to its real and imaginary part?
Gf (s) = Hfilter(s) * G(s)
I have seen some function like cont2discrete or scipy.signal.bilinear but I'm not sure if there is another way of implementation.
Thanks
python filter signal-processing discretization
asked Nov 20 '18 at 1:46
Amir Reza JalaliAmir Reza Jalali
438
add a comment |
I want to know if I have the first-order Chebyshev filter response as below:
H_filter(s) = 1/(-1-s) = real_H_filter (s) + j Imag_H_filter(s)
and also I have my signal as below:
G(s)= Gr (s) + j Gi (s)
How can I discretize the signal and filter by frequency rate of for example 0.0001 rad/s
and then apply the filter to signal to get the filtered signal in Python?
The filtered signal should be looked like below which can easily be decomposed to its real and imaginary part?
Gf (s) = Hfilter(s) * G(s)
I have seen some function like cont2discrete or scipy.signal.bilinear but I'm not sure if there is another way of implementation.
Thanks
python filter signal-processing discretization
asked Nov 20 '18 at 1:46
Amir Reza JalaliAmir Reza Jalali
438
add a comment |
I want to know if I have the first-order Chebyshev filter response as below:
H_filter(s) = 1/(-1-s) = real_H_filter (s) + j Imag_H_filter(s)
and also I have my signal as below:
G(s)= Gr (s) + j Gi (s)
How can I discretize the signal and filter by frequency rate of for example 0.0001 rad/s
and then apply the filter to signal to get the filtered signal in Python?
The filtered signal should be looked like below which can easily be decomposed to its real and imaginary part?
Gf (s) = Hfilter(s) * G(s)
I have seen some function like cont2discrete or scipy.signal.bilinear but I'm not sure if there is another way of implementation.
Thanks
python filter signal-processing discretization
asked Nov 20 '18 at 1:46
Amir Reza JalaliAmir Reza Jalali
438
I want to know if I have the first-order Chebyshev filter response as below:
H_filter(s) = 1/(-1-s) = real_H_filter (s) + j Imag_H_filter(s)
and also I have my signal as below:
G(s)= Gr (s) + j Gi (s)
How can I discretize the signal and filter by frequency rate of for example 0.0001 rad/s
and then apply the filter to signal to get the filtered signal in Python?
The filtered signal should be looked like below which can easily be decomposed to its real and imaginary part?
Gf (s) = Hfilter(s) * G(s)
I have seen some function like cont2discrete or scipy.signal.bilinear but I'm not sure if there is another way of implementation.
Thanks
python filter signal-processing discretization
python filter signal-processing discretization
asked Nov 20 '18 at 1:46
Amir Reza JalaliAmir Reza Jalali
438
asked Nov 20 '18 at 1:46
Amir Reza JalaliAmir Reza Jalali
438
asked Nov 20 '18 at 1:46
Amir Reza JalaliAmir Reza Jalali
438
asked Nov 20 '18 at 1:46
Amir Reza JalaliAmir Reza Jalali
438
asked Nov 20 '18 at 1:46
Amir Reza JalaliAmir Reza Jalali
438
438
add a comment |
add a comment |
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