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#
# Copyright 2005,2007,2012 Free Software Foundation, Inc.
#
# This file is part of GNU Radio
#
# GNU Radio is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3, or (at your option)
# any later version.
#
# GNU Radio is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with GNU Radio; see the file COPYING. If not, write to
# the Free Software Foundation, Inc., 51 Franklin Street,
# Boston, MA 02110-1301, USA.
#
from gnuradio import gr, filter
import math
#
# 1
# H(s) = -------
# 1 + s
#
# tau is the RC time constant.
# critical frequency: w_p = 1/tau
#
# We prewarp and use the bilinear z-transform to get our IIR coefficients.
# See "Digital Signal Processing: A Practical Approach" by Ifeachor and Jervis
#
class fm_deemph(gr.hier_block2):
"""
FM Deemphasis IIR filter.
"""
def __init__(self, fs, tau=75e-6):
"""
Args:
fs: sampling frequency in Hz (float)
tau: Time constant in seconds (75us in US, 50us in EUR) (float)
"""
gr.hier_block2.__init__(self, "fm_deemph",
gr.io_signature(1, 1, gr.sizeof_float), # Input signature
gr.io_signature(1, 1, gr.sizeof_float)) # Output signature
w_p = 1/tau
w_pp = math.tan(w_p / (fs * 2)) # prewarped analog freq
a1 = (w_pp - 1)/(w_pp + 1)
b0 = w_pp/(1 + w_pp)
b1 = b0
btaps = [b0, b1]
ataps = [1, a1]
if 0:
print "btaps =", btaps
print "ataps =", ataps
global plot1
plot1 = gru.gnuplot_freqz(gru.freqz(btaps, ataps), fs, True)
deemph = filter.iir_filter_ffd(btaps, ataps)
self.connect(self, deemph, self)
#
# 1 + s*t1
# H(s) = ----------
# 1 + s*t2
#
# I think this is the right transfer function.
#
#
# This fine ASCII rendition is based on Figure 5-15
# in "Digital and Analog Communication Systems", Leon W. Couch II
#
#
# R1
# +-----||------+
# | |
# o------+ +-----+--------o
# | C1 | |
# +----/\/\/\/--+ \
# /
# \ R2
# /
# \
# |
# o--------------------------+--------o
#
# f1 = 1/(2*pi*t1) = 1/(2*pi*R1*C)
#
# 1 R1 + R2
# f2 = ------- = ------------
# 2*pi*t2 2*pi*R1*R2*C
#
# t1 is 75us in US, 50us in EUR
# f2 should be higher than our audio bandwidth.
#
#
# The Bode plot looks like this:
#
#
# /----------------
# /
# / <-- slope = 20dB/decade
# /
# -------------/
# f1 f2
#
# We prewarp and use the bilinear z-transform to get our IIR coefficients.
# See "Digital Signal Processing: A Practical Approach" by Ifeachor and Jervis
#
class fm_preemph(gr.hier_block2):
"""
FM Preemphasis IIR filter.
"""
def __init__(self, fs, tau=75e-6):
"""
Args:
fs: sampling frequency in Hz (float)
tau: Time constant in seconds (75us in US, 50us in EUR) (float)
"""
gr.hier_block2.__init__(self, "fm_deemph",
gr.io_signature(1, 1, gr.sizeof_float), # Input signature
gr.io_signature(1, 1, gr.sizeof_float)) # Output signature
# FIXME make this compute the right answer
btaps = [1]
ataps = [1]
if 0:
print "btaps =", btaps
print "ataps =", ataps
global plot2
plot2 = gru.gnuplot_freqz(gru.freqz(btaps, ataps), fs, True)
preemph = filter.iir_filter_ffd(btaps, ataps)
self.connect(self, preemph, self)
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