How to normalize a signal along the frequency axis w [0, 1]
I have a signal in the frequency domain (G in my code). I want to normalize it along the frequency axis w [0, 1].
After that, signal will be discretized at ∆w = 0.0001wa up to available
frequency wa = 105 rad/s.
I don't have any idea that how can I normalized my signal along the frequency axis to have the "w" between 0 to 1. ( with the information that I have from my problem).
Thanks for any help or suggestion.
from scipy import signal
import sympy as sp
import matplotlib.pyplot as plt
from scipy.signal import freqs, iirfilter, bilinear, cont2discrete, TransferFunction, hilbert
import numpy as np
import math
wa = 100000
discrete_wa = np.arange(-wa, wa, 0.0001*wa)
def G (w):
G = (((cr1+ 1j*ci1)/(1j*w -(pr1+1j*pi1))) + ((cr2+ 1j*ci2)/(1j*w -(pr2+1j*pi2))) + ((cr3+ 1j*ci3)/(1j*w -(pr1+1j*pi1))))
return G
cr1 = 100;
ci1 = 0;
pr1 = -50 ;
pi1= 200;
cr2 = 1000;
ci2 = 0;
pr2 = -1000 ;
pi2 = 3000;
cr3 = 10000;
ci3 = 0;
pr3 = -7000;
pi3 = 11000;
def F (w):
F = ((1)/(-1-1j*w))
return F
g_dis = [G_(value) for value in discrete_wa]
python filter filtering normalization frequency
asked Nov 26 '18 at 21:21
Amir Reza JalaliAmir Reza Jalali
438
add a comment |
I have a signal in the frequency domain (G in my code). I want to normalize it along the frequency axis w [0, 1].
After that, signal will be discretized at ∆w = 0.0001wa up to available
frequency wa = 105 rad/s.
I don't have any idea that how can I normalized my signal along the frequency axis to have the "w" between 0 to 1. ( with the information that I have from my problem).
Thanks for any help or suggestion.
from scipy import signal
import sympy as sp
import matplotlib.pyplot as plt
from scipy.signal import freqs, iirfilter, bilinear, cont2discrete, TransferFunction, hilbert
import numpy as np
import math
wa = 100000
discrete_wa = np.arange(-wa, wa, 0.0001*wa)
def G (w):
G = (((cr1+ 1j*ci1)/(1j*w -(pr1+1j*pi1))) + ((cr2+ 1j*ci2)/(1j*w -(pr2+1j*pi2))) + ((cr3+ 1j*ci3)/(1j*w -(pr1+1j*pi1))))
return G
cr1 = 100;
ci1 = 0;
pr1 = -50 ;
pi1= 200;
cr2 = 1000;
ci2 = 0;
pr2 = -1000 ;
pi2 = 3000;
cr3 = 10000;
ci3 = 0;
pr3 = -7000;
pi3 = 11000;
def F (w):
F = ((1)/(-1-1j*w))
return F
g_dis = [G_(value) for value in discrete_wa]
python filter filtering normalization frequency
asked Nov 26 '18 at 21:21
Amir Reza JalaliAmir Reza Jalali
438
add a comment |
I have a signal in the frequency domain (G in my code). I want to normalize it along the frequency axis w [0, 1].
After that, signal will be discretized at ∆w = 0.0001wa up to available
frequency wa = 105 rad/s.
I don't have any idea that how can I normalized my signal along the frequency axis to have the "w" between 0 to 1. ( with the information that I have from my problem).
Thanks for any help or suggestion.
from scipy import signal
import sympy as sp
import matplotlib.pyplot as plt
from scipy.signal import freqs, iirfilter, bilinear, cont2discrete, TransferFunction, hilbert
import numpy as np
import math
wa = 100000
discrete_wa = np.arange(-wa, wa, 0.0001*wa)
def G (w):
G = (((cr1+ 1j*ci1)/(1j*w -(pr1+1j*pi1))) + ((cr2+ 1j*ci2)/(1j*w -(pr2+1j*pi2))) + ((cr3+ 1j*ci3)/(1j*w -(pr1+1j*pi1))))
return G
cr1 = 100;
ci1 = 0;
pr1 = -50 ;
pi1= 200;
cr2 = 1000;
ci2 = 0;
pr2 = -1000 ;
pi2 = 3000;
cr3 = 10000;
ci3 = 0;
pr3 = -7000;
pi3 = 11000;
def F (w):
F = ((1)/(-1-1j*w))
return F
g_dis = [G_(value) for value in discrete_wa]
python filter filtering normalization frequency
asked Nov 26 '18 at 21:21
Amir Reza JalaliAmir Reza Jalali
438
I have a signal in the frequency domain (G in my code). I want to normalize it along the frequency axis w [0, 1].
After that, signal will be discretized at ∆w = 0.0001wa up to available
frequency wa = 105 rad/s.
I don't have any idea that how can I normalized my signal along the frequency axis to have the "w" between 0 to 1. ( with the information that I have from my problem).
Thanks for any help or suggestion.
from scipy import signal
import sympy as sp
import matplotlib.pyplot as plt
from scipy.signal import freqs, iirfilter, bilinear, cont2discrete, TransferFunction, hilbert
import numpy as np
import math
wa = 100000
discrete_wa = np.arange(-wa, wa, 0.0001*wa)
def G (w):
G = (((cr1+ 1j*ci1)/(1j*w -(pr1+1j*pi1))) + ((cr2+ 1j*ci2)/(1j*w -(pr2+1j*pi2))) + ((cr3+ 1j*ci3)/(1j*w -(pr1+1j*pi1))))
return G
cr1 = 100;
ci1 = 0;
pr1 = -50 ;
pi1= 200;
cr2 = 1000;
ci2 = 0;
pr2 = -1000 ;
pi2 = 3000;
cr3 = 10000;
ci3 = 0;
pr3 = -7000;
pi3 = 11000;
def F (w):
F = ((1)/(-1-1j*w))
return F
g_dis = [G_(value) for value in discrete_wa]
python filter filtering normalization frequency
python filter filtering normalization frequency
asked Nov 26 '18 at 21:21
Amir Reza JalaliAmir Reza Jalali
438
asked Nov 26 '18 at 21:21
Amir Reza JalaliAmir Reza Jalali
438
edited Nov 26 '18 at 21:27
Amir Reza Jalali
asked Nov 26 '18 at 21:21
Amir Reza JalaliAmir Reza Jalali
438
asked Nov 26 '18 at 21:21
Amir Reza JalaliAmir Reza Jalali
438
asked Nov 26 '18 at 21:21
Amir Reza JalaliAmir Reza Jalali
438
438
add a comment |
add a comment |
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