Created
April 15, 2015 13:11
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Simple LMS equaliser in Python
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#!/usr/bin/env python | |
import numpy as np | |
import matplotlib.pyplot as plt | |
import pdb | |
def lms(u, d, M, step, leak=0, initCoeffs=None, N=None, returnCoeffs=False): | |
if N is None: | |
N = len(u)-M+1 | |
initCoeffs = np.zeros(M) | |
# Initialization | |
y = np.zeros(N) # Filter output | |
e = np.zeros(N) # Error signal | |
w = initCoeffs # Initialise equaliser | |
leakstep = (1 - step*leak) | |
if returnCoeffs: | |
W = np.zeros((N, M)) # Matrix to hold coeffs for each equaliser step | |
# Equalise | |
for n in xrange(N): | |
x = np.flipud(u[n:n+M]) # | |
y[n] = np.dot(x, w) | |
e[n] = d[n+M-1] - y[n] | |
w = leakstep * w + step * x * e[n] | |
y[n] = np.dot(x, w) | |
if returnCoeffs: | |
W[n] = w | |
if returnCoeffs: | |
w = W | |
return y, e, w | |
np.random.seed(1337) | |
ulen = 2000 | |
coeff = np.concatenate(([1], np.zeros(10), [-0.9], np.zeros(7), [0.1])) | |
u = np.random.randn(ulen) | |
d = np.convolve(u, coeff) | |
M = 20 # No. of taps | |
step = 0.003 # Step size | |
y, e, w = lms(u, d, M, step) | |
print np.allclose(w, coeff) | |
plt.figure() | |
plt.subplot(1,1,1) | |
plt.plot(np.abs(e[0:400])) | |
plt.show() | |
#pdb.set_trace() | |
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