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1 // Copyright 2008-2010, Thomas Walters
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2 //
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3 // AIM-C: A C++ implementation of the Auditory Image Model
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4 // http://www.acousticscale.org/AIMC
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5 //
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6 // This program is free software: you can redistribute it and/or modify
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7 // it under the terms of the GNU General Public License as published by
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8 // the Free Software Foundation, either version 3 of the License, or
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9 // (at your option) any later version.
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10 //
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11 // This program is distributed in the hope that it will be useful,
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12 // but WITHOUT ANY WARRANTY; without even the implied warranty of
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13 // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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14 // GNU General Public License for more details.
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15 //
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16 // You should have received a copy of the GNU General Public License
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17 // along with this program. If not, see <http://www.gnu.org/licenses/>.
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18
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19 /*! \file
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20 * \brief Dick Lyon's Pole-Zero Filter Cascade - implemented as an AIM-C
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21 * module by Tom Walters from the AIM-MAT module based on Dick Lyon's code
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22 */
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23
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24 /*! \author Thomas Walters <tom@acousticscale.org>
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25 * \date created 2008/02/05
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26 * \version \$Id: ModulePZFC.cc 4 2010-02-03 18:44:58Z tcw $
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27 */
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28
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29 #include "Support/ERBTools.h"
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30
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31 #include "Modules/BMM/ModulePZFC.h"
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32
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33 namespace aimc {
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34 ModulePZFC::ModulePZFC(Parameters *parameters) : Module(parameters) {
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35 module_identifier_ = "pzfc";
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36 module_type_ = "bmm";
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37 module_description_ = "Pole-Zero Filter Cascade";
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38 module_version_ = "$Id: ModulePZFC.cc 4 2010-02-03 18:44:58Z tcw $";
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39
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40 // Get parameter values, setting default values where necessary
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41 // Each parameter is set here only if it has not already been set elsewhere.
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42 cf_max_ = parameters_->DefaultFloat("pzfc.highest_frequency", 6000.0f);
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43 cf_min_ = parameters_->DefaultFloat("pzfc.lowest_frequency", 100.0f);
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44 pole_damping_ = parameters_->DefaultFloat("pzfc.pole_damping", 0.12f);
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45 zero_damping_ = parameters_->DefaultFloat("pzfc.zero_damping", 0.2f);
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46 zero_factor_ = parameters_->DefaultFloat("pzfc.zero_factor", 1.4f);
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47 step_factor_ = parameters_->DefaultFloat("pzfc.step_factor", 1.0f/3.0f);
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48 bandwidth_over_cf_ = parameters_->DefaultFloat("pzfc.bandwidth_over_cf",
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49 0.11f);
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50 min_bandwidth_hz_ = parameters_->DefaultFloat("pzfc.min_bandwidth_hz",
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51 27.0f);
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52 agc_factor_ = parameters_->DefaultFloat("pzfc.agc_factor", 12.0f);
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53 do_agc_step_ = parameters_->DefaultBool("pzfc.do_agc", true);
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54
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55 detect_.resize(0);
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56 }
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57
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58 ModulePZFC::~ModulePZFC() {
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59 }
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60
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61 bool ModulePZFC::InitializeInternal(const SignalBank &input) {
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62 // Make local convenience copies of some variables
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63 sample_rate_ = input.sample_rate();
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64 buffer_length_ = input.buffer_length();
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65 channel_count_ = 0;
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66
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67 // Prepare the coefficients and also the output SignalBank
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68 if (!SetPZBankCoeffs())
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69 return false;
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70
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71 // The output signal bank should be set up by now.
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72 if (!output_.initialized())
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73 return false;
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74
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75 // This initialises all buffers which can be modified by Process()
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76 ResetInternal();
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77
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78 return true;
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79 }
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80
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81 void ModulePZFC::ResetInternal() {
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82 // These buffers may be actively modified by the algorithm
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83 agc_state_.clear();
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84 agc_state_.resize(channel_count_);
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85 for (int i = 0; i < channel_count_; ++i) {
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86 agc_state_[i].clear();
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87 agc_state_[i].resize(agc_stage_count_, 0.0f);
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88 }
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89
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90 state_1_.clear();
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91 state_1_.resize(channel_count_, 0.0f);
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92
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93 state_2_.clear();
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94 state_2_.resize(channel_count_, 0.0f);
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95
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96 previous_out_.clear();
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97 previous_out_.resize(channel_count_, 0.0f);
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98
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99 pole_damps_mod_.clear();
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100 pole_damps_mod_.resize(channel_count_, 0.0f);
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101
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102 inputs_.clear();
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103 inputs_.resize(channel_count_, 0.0f);
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104
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105 // Init AGC
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106 AGCDampStep();
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107 // pole_damps_mod_ and agc_state_ are now be initialized
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108
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109 // Modify the pole dampings and AGC state slightly from their values in
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110 // silence in case the input is abuptly loud.
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111 for (int i = 0; i < channel_count_; ++i) {
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112 pole_damps_mod_[i] += 0.05f;
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113 for (int j = 0; j < agc_stage_count_; ++j)
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114 agc_state_[i][j] += 0.05f;
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115 }
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116
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117 last_input_ = 0.0f;
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118 }
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119
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120 bool ModulePZFC::SetPZBankCoeffsERBFitted() {
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121 float parameter_values[3 * 7] = {
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122 // Filed, Nfit = 524, 11-3 parameters, PZFC, cwt 0, fit time 9915 sec
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123 1.14827, 0.00000, 0.00000, // % SumSqrErr= 10125.41
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124 0.53571, -0.70128, 0.63246, // % RMSErr = 2.81586
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125 0.76779, 0.00000, 0.00000, // % MeanErr = 0.00000
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126 // Inf 0.00000 0.00000 % RMSCost = NaN
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127 0.00000, 0.00000, 0.00000,
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128 6.00000, 0.00000, 0.00000,
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129 1.08869, -0.09470, 0.07844,
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130 10.56432, 2.52732, 1.86895
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131 // -3.45865 -1.31457 3.91779 % Kv
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132 };
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133
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134 // Precalculate the number of channels required - this method is ugly but it
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135 // was the quickest way of converting from MATLAB as the step factor between
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136 // channels can vary quadratically with pole frequency...
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137
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138 // Normalised maximum pole frequency
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139 float pole_frequency = cf_max_ / sample_rate_ * (2.0f * M_PI);
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140
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141 channel_count_ = 0;
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142 while ((pole_frequency / (2.0f * M_PI)) * sample_rate_ > cf_min_) {
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143 float frequency = pole_frequency / (2.0f * M_PI) * sample_rate_;
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144 float f_dep = ERBTools::Freq2ERB(frequency)
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145 / ERBTools::Freq2ERB(1000.0f) - 1.0f;
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146 float bw = ERBTools::Freq2ERBw(pole_frequency
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147 / (2.0f * M_PI) * sample_rate_);
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148 float step_factor = 1.0f
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149 / (parameter_values[4*3] + parameter_values[4 * 3 + 1]
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150 * f_dep + parameter_values[4 * 3 + 2] * f_dep * f_dep); // 1/n2
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151 pole_frequency -= step_factor * (bw * (2.0f * M_PI) / sample_rate_);
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152 channel_count_++;
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153 }
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154
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155 // Now the number of channels is known, various buffers for the filterbank
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156 // coefficients can be initialised
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157 pole_dampings_.clear();
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158 pole_dampings_.resize(channel_count_, 0.0f);
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159 pole_frequencies_.clear();
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160 pole_frequencies_.resize(channel_count_, 0.0f);
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161
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162 // Direct-form coefficients
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163 za0_.clear();
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164 za0_.resize(channel_count_, 0.0f);
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165 za1_.clear();
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166 za1_.resize(channel_count_, 0.0f);
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167 za2_.clear();
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168 za2_.resize(channel_count_, 0.0f);
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169
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170 // The output signal bank
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171 output_.Initialize(channel_count_, buffer_length_, sample_rate_);
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172
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173 // Reset the pole frequency to maximum
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174 pole_frequency = cf_max_ / sample_rate_ * (2.0f * M_PI);
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175
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176 for (int i = channel_count_ - 1; i > -1; --i) {
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177 // Store the normalised pole frequncy
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178 pole_frequencies_[i] = pole_frequency;
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179
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180 // Calculate the real pole frequency from the normalised pole frequency
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181 float frequency = pole_frequency / (2.0f * M_PI) * sample_rate_;
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182
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183 // Store the real pole frequency as the 'centre frequency' of the filterbank
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184 // channel
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185 output_.set_centre_frequency(i, frequency);
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186
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187 // From PZFC_Small_Signal_Params.m { From PZFC_Params.m {
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188 float DpndF = ERBTools::Freq2ERB(frequency)
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189 / ERBTools::Freq2ERB(1000.0f) - 1.0f;
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190
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191 float p[8]; // Parameters (short name for ease of reading)
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192
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193 // Use parameter_values to recover the parameter values for this frequency
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194 for (int param = 0; param < 7; ++param)
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195 p[param] = parameter_values[param * 3]
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196 + parameter_values[param * 3 + 1] * DpndF
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197 + parameter_values[param * 3 + 2] * DpndF * DpndF;
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198
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199 // Calculate the final parameter
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200 p[7] = p[1] * pow(10.0f, (p[2] / (p[1] * p[4])) * (p[6] - 60.0f) / 20.0f);
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201 if (p[7] < 0.2f)
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202 p[7] = 0.2f;
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203
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204 // Nominal bandwidth at this frequency
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205 float fERBw = ERBTools::Freq2ERBw(frequency);
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206
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207 // Pole bandwidth
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208 float fPBW = ((p[7] * fERBw * (2 * M_PI) / sample_rate_) / 2)
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209 * pow(p[4], 0.5f);
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210
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211 // Pole damping
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212 float pole_damping = fPBW / sqrt(pow(pole_frequency, 2) + pow(fPBW, 2));
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213
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214 // Store the pole damping
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215 pole_dampings_[i] = pole_damping;
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216
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217 // Zero bandwidth
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218 float fZBW = ((p[0] * p[5] * fERBw * (2 * M_PI) / sample_rate_) / 2)
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219 * pow(p[4], 0.5f);
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220
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221 // Zero frequency
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222 float zero_frequency = p[5] * pole_frequency;
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223
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224 if (zero_frequency > M_PI)
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225 LOG_ERROR(_T("Warning: Zero frequency is above the Nyquist frequency "
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226 "in ModulePZFC(), continuing anyway but results may not "
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227 "be accurate."));
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228
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229 // Zero damping
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230 float fZDamp = fZBW / sqrt(pow(zero_frequency, 2) + pow(fZBW, 2));
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231
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232 // Impulse-invariance mapping
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233 float fZTheta = zero_frequency * sqrt(1.0f - pow(fZDamp, 2));
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234 float fZRho = exp(-fZDamp * zero_frequency);
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235
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236 // Direct-form coefficients
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237 float fA1 = -2.0f * fZRho * cos(fZTheta);
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238 float fA2 = fZRho * fZRho;
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239
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240 // Normalised to unity gain at DC
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241 float fASum = 1.0f + fA1 + fA2;
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242 za0_[i] = 1.0f / fASum;
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243 za1_[i] = fA1 / fASum;
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244 za2_[i] = fA2 / fASum;
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245
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246 // Subtract step factor (1/n2) times current bandwidth from the pole
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247 // frequency
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248 pole_frequency -= ((1.0f / p[4])
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249 * (fERBw * (2.0f * M_PI) / sample_rate_));
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250 }
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251 return true;
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252 }
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253
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254 bool ModulePZFC::SetPZBankCoeffs() {
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255 /*! \todo Re-implement the alternative parameter settings
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256 */
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257 if (!SetPZBankCoeffsERBFitted())
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258 return false;
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259
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260 /*! \todo Make fMindamp and fMaxdamp user-settable?
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261 */
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262 mindamp_ = 0.18f;
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263 maxdamp_ = 0.4f;
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264
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265 rmin_.resize(channel_count_);
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266 rmax_.resize(channel_count_);
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267 xmin_.resize(channel_count_);
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268 xmax_.resize(channel_count_);
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269
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270 for (int c = 0; c < channel_count_; ++c) {
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271 // Calculate maximum and minimum damping options
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272 rmin_[c] = exp(-mindamp_ * pole_frequencies_[c]);
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273 rmax_[c] = exp(-maxdamp_ * pole_frequencies_[c]);
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274
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275 xmin_[c] = rmin_[c] * cos(pole_frequencies_[c]
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276 * pow((1-pow(mindamp_, 2)), 0.5f));
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277 xmax_[c] = rmax_[c] * cos(pole_frequencies_[c]
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278 * pow((1-pow(maxdamp_, 2)), 0.5f));
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279 }
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280
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281 // Set up AGC parameters
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282 agc_stage_count_ = 4;
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283 agc_epsilons_.resize(agc_stage_count_);
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284 agc_epsilons_[0] = 0.0064f;
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285 agc_epsilons_[1] = 0.0016f;
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286 agc_epsilons_[2] = 0.0004f;
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287 agc_epsilons_[3] = 0.0001f;
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288
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289 agc_gains_.resize(agc_stage_count_);
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290 agc_gains_[0] = 1.0f;
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291 agc_gains_[1] = 1.4f;
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292 agc_gains_[2] = 2.0f;
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293 agc_gains_[3] = 2.8f;
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294
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295 float mean_agc_gain = 0.0f;
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296 for (int c = 0; c < agc_stage_count_; ++c)
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297 mean_agc_gain += agc_gains_[c];
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298 mean_agc_gain /= static_cast<float>(agc_stage_count_);
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299
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300 for (int c = 0; c < agc_stage_count_; ++c)
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301 agc_gains_[c] /= mean_agc_gain;
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302
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303 return true;
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304 }
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305
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306 void ModulePZFC::AGCDampStep() {
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307 if (detect_.size() == 0) {
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308 // If detect_ is not initialised, it means that the AGC is not set up.
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309 // Set up now.
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310 /*! \todo Make a separate InitAGC function which does this.
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311 */
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312 detect_.resize(channel_count_);
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313 for (int c = 0; c < channel_count_; ++c)
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314 detect_[c] = 1.0f;
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315
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316 float fDetectZero = DetectFun(0.0f);
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317 for (int c = 0; c < channel_count_; c++)
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318 detect_[c] *= fDetectZero;
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319
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320 for (int c = 0; c < channel_count_; c++)
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321 for (int st = 0; st < agc_stage_count_; st++)
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322 agc_state_[c][st] = (1.2f * detect_[c] * agc_gains_[st]);
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323 }
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324
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325 float fAGCEpsLeft = 0.3f;
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326 float fAGCEpsRight = 0.3f;
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327
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328 for (int c = channel_count_ - 1; c > -1; --c) {
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329 for (int st = 0; st < agc_stage_count_; ++st) {
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330 // This bounds checking is ugly and wasteful, and in an inner loop.
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331 // If this algorithm is slow, this is why!
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332 /*! \todo Proper non-ugly bounds checking in AGCDampStep()
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333 */
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334 float fPrevAGCState;
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335 float fCurrAGCState;
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336 float fNextAGCState;
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337
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338 if (c < channel_count_ - 1)
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339 fPrevAGCState = agc_state_[c + 1][st];
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340 else
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341 fPrevAGCState = agc_state_[c][st];
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342
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343 fCurrAGCState = agc_state_[c][st];
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344
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345 if (c > 0)
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346 fNextAGCState = agc_state_[c - 1][st];
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347 else
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348 fNextAGCState = agc_state_[c][st];
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349
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350 // Spatial smoothing
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351 /*! \todo Something odd is going on here
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352 * I think this line is not quite right.
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353 */
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354 float agc_avg = fAGCEpsLeft * fPrevAGCState
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355 + (1.0f - fAGCEpsLeft - fAGCEpsRight) * fCurrAGCState
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356 + fAGCEpsRight * fNextAGCState;
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357 // Temporal smoothing
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358 agc_state_[c][st] = agc_avg * (1.0f - agc_epsilons_[st])
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359 + agc_epsilons_[st] * detect_[c] * agc_gains_[st];
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360 }
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361 }
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362
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363 float fOffset = 1.0f - agc_factor_ * DetectFun(0.0f);
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364
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365 for (int i = 0; i < channel_count_; ++i) {
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366 float fAGCStateMean = 0.0f;
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367 for (int j = 0; j < agc_stage_count_; ++j)
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368 fAGCStateMean += agc_state_[i][j];
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369
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370 fAGCStateMean /= static_cast<float>(agc_stage_count_);
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371
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372 pole_damps_mod_[i] = pole_dampings_[i] *
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373 (fOffset + agc_factor_ * fAGCStateMean);
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374 }
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375 }
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376
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377 float ModulePZFC::DetectFun(float fIN) {
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378 if (fIN < 0.0f)
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379 fIN = 0.0f;
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380 float fDetect = Minimum(1.0f, fIN);
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381 float fA = 0.25f;
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382 return fA * fIN + (1.0f - fA) * (fDetect - pow(fDetect, 3) / 3.0f);
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383 }
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384
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385 inline float ModulePZFC::Minimum(float a, float b) {
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386 if (a < b)
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387 return a;
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388 else
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389 return b;
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390 }
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391
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392 void ModulePZFC::Process(const SignalBank& input) {
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393 // Set the start time of the output buffer
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394 output_.set_start_time(input.start_time());
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395
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396 for (int iSample = 0; iSample < input.buffer_length(); ++iSample) {
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397 float fInput = input[0][iSample];
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398
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399 // Lowpass filter the input with a zero at PI
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400 fInput = 0.5f * fInput + 0.5f * last_input_;
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401 last_input_ = input[0][iSample];
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402
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403 inputs_[channel_count_ - 1] = fInput;
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404 for (int c = 0; c < channel_count_ - 1; ++c)
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405 inputs_[c] = previous_out_[c + 1];
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406
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407 // PZBankStep2
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408 // to save a bunch of divides
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409 float damp_rate = 1.0f / (maxdamp_ - mindamp_);
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410
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411 for (int c = channel_count_ - 1; c > -1; --c) {
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412 float interp_factor = (pole_damps_mod_[c]
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413 - mindamp_) * damp_rate;
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414
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415 float x = xmin_[c] + (xmax_[c] - xmin_[c]) * interp_factor;
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416 float r = rmin_[c] + (rmax_[c] - rmin_[c]) * interp_factor;
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417
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418 // optional improvement to constellation adds a bit to r
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419 float fd = pole_frequencies_[c] * pole_damps_mod_[c];
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420 // quadratic for small values, then linear
|
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421 r = r + 0.25f * fd * Minimum(0.05f, fd);
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422
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423 float zb1 = -2.0f * x;
|
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424 float zb2 = r * r;
|
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425
|
tomwalters@268
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426 /* canonic poles but with input provided where unity DC gain is assured
|
tomwalters@268
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427 * (mean value of state is always equal to mean value of input)
|
tomwalters@268
|
428 */
|
tomwalters@268
|
429 float new_state = inputs_[c] - (state_1_[c] - inputs_[c]) * zb1
|
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|
430 - (state_2_[c] - inputs_[c]) * zb2;
|
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|
431
|
tomwalters@268
|
432 // canonic zeros part as before:
|
tomwalters@268
|
433 float output = za0_[c] * new_state + za1_[c] * state_1_[c]
|
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|
434 + za2_[c] * state_2_[c];
|
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|
435
|
tomwalters@268
|
436 // cubic compression nonlinearity
|
tomwalters@268
|
437 output = output - 0.0001f * pow(output, 3);
|
tomwalters@268
|
438
|
tomwalters@268
|
439 output_.set_sample(c, iSample, output);
|
tomwalters@268
|
440 detect_[c] = DetectFun(output);
|
tomwalters@268
|
441 state_2_[c] = state_1_[c];
|
tomwalters@268
|
442 state_1_[c] = new_state;
|
tomwalters@268
|
443 }
|
tomwalters@268
|
444
|
tomwalters@268
|
445 if (do_agc_step_)
|
tomwalters@268
|
446 AGCDampStep();
|
tomwalters@268
|
447
|
tomwalters@268
|
448 for (int c = 0; c < channel_count_; ++c)
|
tomwalters@268
|
449 previous_out_[c] = output_[c][iSample];
|
tomwalters@268
|
450 }
|
tomwalters@268
|
451 PushOutput();
|
tomwalters@268
|
452 }
|
tomwalters@268
|
453 } // namespace aimc
|