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28 lines
732 B
Python
28 lines
732 B
Python
from amodem import train
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from amodem import dsp
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from numpy.linalg import norm
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import numpy as np
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def test_fir():
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a = [1, 0.8, -0.1, 0, 0]
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tx = train.equalizer
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rx = dsp.lfilter(x=tx, b=[1], a=a)
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h_ = dsp.estimate(x=rx, y=tx, order=len(a))
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tx_ = dsp.lfilter(x=rx, b=h_, a=[1])
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assert norm(h_ - a) < 1e-12
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assert (norm(tx - tx_) / norm(tx)) < 1e-12
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def test_iir():
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alpha = 0.1
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b = [1, -alpha]
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tx = train.equalizer
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rx = dsp.lfilter(x=tx, b=b, a=[1])
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h_ = dsp.estimate(x=rx, y=tx, order=20)
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tx_ = dsp.lfilter(x=rx, b=h_, a=[1])
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h_expected = np.array([alpha ** i for i in range(len(h_))])
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assert norm(h_ - h_expected) < 1e-12
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assert (norm(tx - tx_) / norm(tx)) < 1e-12
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