Commit 795b254b authored by Jonathan Wilkes's avatar Jonathan Wilkes
Browse files

sync iem_adaptfilt library with Pd-l2ork (must have missed a commit awhile back)

parent 28910255
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#X text 4 495 filtered output signal;
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#X text 300 146 +;
#X text 243 146 x[n-i];
#X text 174 135 my(n) =;
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#X text 660 364 (C) 2010 \, t.musil & m.guldenschuh \, IEM \, Graz
\, Austria;
#X text 688 377 [musil | guldenschuh]_AT_iem.at;
#X text 662 173 Normalized Least Mean Square with separated error and
adaption reference input (linear adaptive FIR-filter);
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......@@ -163,7 +163,7 @@ static t_int *NLMSCC_tilde_perform(t_int *w)
t_float *wmax_filt_coeff = x->x_wmax_array_mem_beg;
t_float my, my_err, sum;
t_float beta = x->x_beta;
t_float gamma = x->x_gamma;
t_float gammax = x->x_gamma;
t_int i, j, update_counter;
t_int update = x->x_update;
t_int ord8=n_order&0xfffffff8;
......@@ -230,7 +230,7 @@ static t_int *NLMSCC_tilde_perform(t_int *w)
}
for(j=0; j<ord_residual; j++) // residual
sum += read_in_hist[-j] * read_in_hist[-j]; // [-j] only valid for Musil's double buffer structure
sum += gamma * gamma * (float)n_order; // convert gamma corresponding to filter order
sum += gammax * gammax * (float)n_order; // convert gammax corresponding to filter order
my = beta / sum;// calculate mue
......@@ -312,7 +312,7 @@ static void *NLMSCC_tilde_new(t_symbol *s, t_int argc, t_atom *argv)
t_symbol *wmin_name;
t_symbol *wmax_name;
t_float beta=0.1f;
t_float gamma=0.00001f;
t_float gammax=0.00001f;
if((argc >= 6) &&
IS_A_FLOAT(argv,0) && //IS_A_FLOAT/SYMBOL from iemlib.h
......@@ -324,7 +324,7 @@ static void *NLMSCC_tilde_new(t_symbol *s, t_int argc, t_atom *argv)
{
n_order = (t_int)atom_getintarg(0, argc, argv);
beta = (t_float)atom_getfloatarg(1, argc, argv);
gamma = (t_float)atom_getfloatarg(2, argc, argv);
gammax = (t_float)atom_getfloatarg(2, argc, argv);
w_name = (t_symbol *)atom_getsymbolarg(3, argc, argv);
wmin_name = (t_symbol *)atom_getsymbolarg(4, argc, argv);
wmax_name = (t_symbol *)atom_getsymbolarg(5, argc, argv);
......@@ -334,10 +334,10 @@ static void *NLMSCC_tilde_new(t_symbol *s, t_int argc, t_atom *argv)
if(beta > 2.0f)
beta = 2.0f;
if(gamma < 0.0f)
gamma = 0.0f;
if(gamma > 1.0f)
gamma = 1.0f;
if(gammax < 0.0f)
gammax = 0.0f;
if(gammax > 1.0f)
gammax = 1.0f;
if(n_order < 2)
n_order = 2;
......@@ -353,7 +353,7 @@ static void *NLMSCC_tilde_new(t_symbol *s, t_int argc, t_atom *argv)
x->x_n_order = n_order;
x->x_update = 0;
x->x_beta = beta;
x->x_gamma = gamma;
x->x_gamma = gammax;
// 2 times in and one time desired_in memory allocation (history)
x->x_in_hist = (t_float *)getbytes(2*x->x_n_order*sizeof(t_float));
......@@ -382,7 +382,7 @@ void NLMSCC_tilde_setup(void)
NLMSCC_tilde_class = class_new(gensym("NLMSCC~"), (t_newmethod)NLMSCC_tilde_new, (t_method)NLMSCC_tilde_free,
sizeof(t_NLMSCC_tilde), 0, A_GIMME, 0);
CLASS_MAINSIGNALIN(NLMSCC_tilde_class, t_NLMSCC_tilde, x_msi);
class_addmethod(NLMSCC_tilde_class, (t_method)NLMSCC_tilde_dsp, gensym("dsp"), A_CANT, 0);
class_addmethod(NLMSCC_tilde_class, (t_method)NLMSCC_tilde_dsp, gensym("dsp"), 0);
class_addmethod(NLMSCC_tilde_class, (t_method)NLMSCC_tilde_update, gensym("update"), A_FLOAT, 0); // method: downsampling factor of learning (multiple of 2^N)
class_addmethod(NLMSCC_tilde_class, (t_method)NLMSCC_tilde_beta, gensym("beta"), A_FLOAT, 0); //method: normalized learning rate
class_addmethod(NLMSCC_tilde_class, (t_method)NLMSCC_tilde_gamma, gensym("gamma"), A_FLOAT, 0); // method: dithering noise related to signal
......
/* For information on usage and redistribution, and for a DISCLAIMER OF ALL
* WARRANTIES, see the file, "LICENSE.txt," in this distribution.
NLMS normalized least mean square (LMS) algorithm
lib iem_adaptfilt written by Markus Noisternig & Thomas Musil
noisternig_AT_iem.at; musil_AT_iem.at
(c) Institute of Electronic Music and Acoustics, Graz Austria 2005 */
#include "m_pd.h"
#include "iemlib.h"
#include <math.h>
#include <stdio.h>
#include <string.h>
/* ----------------------- NLMSerr_in~ ------------------------------ */
/* -- Normalized Least Mean Square (linear adaptive FIR-filter) -- */
/* -- first input: reference signal -- */
/* -- second input: desired signal -- */
/* -- the difference to NLMS~ is: we have only one ERROR input instead of desired in minus filter out -- */
/* -- that means there is no feedback -- */
/* for further information on adaptive filter design we refer to */
/* [1] Haykin, "Adaptive Filter Theory", 4th ed, Prentice Hall */
/* [2] Benesty, "Adaptive Signal Processing", Springer */
typedef struct NLMSerr_in_tilde
{
t_object x_obj;// common pd object structure
t_symbol *x_w_array_sym_name;
t_float *x_w_array_mem_beg;
t_float *x_ref_filt_in_hist;// history buffer for input signal reference for internal convolution = filter
t_float *x_ref_adapt_in_hist;// history buffer for input signal reference for internal adapting filter
t_int x_rw_index;// current read-write-index in circular buffer
t_int x_n_order;// order of filter or convolution
t_int x_update;// binary update parameter ON / OFF
t_float x_beta;// learn rate [0 .. 2]
t_float x_gamma;// regularization Parameter = minimum
t_float x_flt_sig_in1;
} t_NLMSerr_in_tilde;
t_class *NLMSerr_in_tilde_class;
static t_float *NLMSerr_in_tilde_check_array(t_symbol *array_sym_name, t_int length)
{
int n_points;
t_garray *a;
t_float *vec;
if(!(a = (t_garray *)pd_findbyclass(array_sym_name, garray_class)))
{
error("%s: no such array for NLMSerr_in~", array_sym_name->s_name);
return((t_float *)0);
}
else if(!garray_getfloatarray(a, &n_points, &vec))
{
error("%s: bad template for NLMSerr_in~", array_sym_name->s_name);
return((t_float *)0);
}
else if(n_points < length)
{
error("%s: bad array-size for NLMSerr_in~: %d", array_sym_name->s_name, n_points);
return((t_float *)0);
}
else
{
return(vec);
}
}
static void NLMSerr_in_tilde_beta(t_NLMSerr_in_tilde *x, t_floatarg f) // learn rate
{
if(f < 0.0f)
f = 0.0f;
if(f > 2.0f)
f = 2.0f;
x->x_beta = f;
}
static void NLMSerr_in_tilde_gamma(t_NLMSerr_in_tilde *x, t_floatarg f) // regularization factor (dither)
{
if(f < 0.0f)
f = 0.0f;
if(f > 1.0f)
f = 1.0f;
x->x_gamma = f;
}
static void NLMSerr_in_tilde_update(t_NLMSerr_in_tilde *x, t_floatarg f) // downsample learn-rate
{
t_int i=1, u = (t_int)f;
if(u != 0)
u = 1;
x->x_update = u;
}
/* ============== DSP ======================= */
static t_int *NLMSerr_in_tilde_perform_zero(t_int *w)
{
t_NLMSerr_in_tilde *x = (t_NLMSerr_in_tilde *)(w[5]);
t_int n = (t_int)(w[6]);
t_float *filt_out = (t_float *)(w[4]);
t_int i;
for(i=0; i<n; i++)
{
*filt_out++ = 0.0f;
}
return (w+7);
}
static t_int *NLMSerr_in_tilde_perform(t_int *w)
{
t_int n = (t_int)(w[6]);
t_NLMSerr_in_tilde *x = (t_NLMSerr_in_tilde *)(w[5]);
t_float *filt_out = (t_float *)(w[4]);// first sig out
t_float *err_in = (t_float *)(w[3]);// third sig in
t_float *ref_adapt_in = (t_float *)(w[2]);// second sig in
t_float *ref_filt_in = (t_float *)(w[1]);// first sig in
t_int n_order = x->x_n_order; /* number of filter-order */
t_int rw_index = x->x_rw_index; /* current read write index in circular buffer */
t_int update = x->x_update;
t_float beta = x->x_beta; /* learn rate */
t_float gammax = x->x_gamma; /* minimum energy */
t_float my, my_err, sum, errin;
t_int i, j, k;
if(!x->x_w_array_mem_beg)
goto NLMSerr_in_tildeperfzero;// this is quick&dirty Musil/Miller style
for(i=0; i<n; i++)// store history and convolve
{
x->x_ref_filt_in_hist[rw_index] = ref_filt_in[i]; // inputs of ref_filt save to history
x->x_ref_adapt_in_hist[rw_index] = ref_adapt_in[i]; // inputs of ref_adapt save to history
errin = err_in[i];
// begin convolution, filter : j++, k--, rw_index = aktueller index fuer lesen schreiben von history und convolution-beginn
sum = 0.0f;
k = rw_index;
for(j=0; j<n_order; j++)
{
sum += x->x_w_array_mem_beg[j] * x->x_ref_filt_in_hist[k];
k--;
if(k < 0)
k = n_order - 1;
}
filt_out[i] = sum;
if(update) // downsampling for learn rate
{
sum = 0.0f;// calculate energy for last n-order samples in filter
k = rw_index;
for(j=0; j<n_order; j++) // unrolling quadrature calc
{
sum += x->x_ref_adapt_in_hist[k] * x->x_ref_adapt_in_hist[k]; // energie
k--;
if(k < 0)
k = n_order - 1;
}
sum += gammax * gammax * (float)n_order; // convert gammax corresponding to filter order
my = beta / sum;// calculate mue
my_err = my * errin;
k = rw_index;
for(j=0; j<n_order; j++) // without unroll
{
x->x_w_array_mem_beg[j] += x->x_ref_adapt_in_hist[k] * my_err;
k--;
if(k < 0)
k = n_order - 1;
}
}
rw_index++;
if(rw_index >= n_order)
rw_index = 0;
}
x->x_rw_index = rw_index; // back to start
return(w+7);
NLMSerr_in_tildeperfzero:
while(n--)
{
*filt_out++ = 0.0f;
}
return(w+7);
}
static void NLMSerr_in_tilde_dsp(t_NLMSerr_in_tilde *x, t_signal **sp)
{
x->x_w_array_mem_beg = NLMSerr_in_tilde_check_array(x->x_w_array_sym_name, x->x_n_order);
if(!x->x_w_array_mem_beg)
dsp_add(NLMSerr_in_tilde_perform_zero, 6, sp[0]->s_vec, sp[1]->s_vec, sp[2]->s_vec, sp[3]->s_vec, x, sp[0]->s_n);
else
dsp_add(NLMSerr_in_tilde_perform, 6, sp[0]->s_vec, sp[1]->s_vec, sp[2]->s_vec, sp[3]->s_vec, x, sp[0]->s_n);
}
/* setup/setdown things */
static void NLMSerr_in_tilde_free(t_NLMSerr_in_tilde *x)
{
freebytes(x->x_ref_filt_in_hist, x->x_n_order*sizeof(t_float));
freebytes(x->x_ref_adapt_in_hist, x->x_n_order*sizeof(t_float));
}
static void *NLMSerr_in_tilde_new(t_symbol *s, t_int argc, t_atom *argv)
{
t_NLMSerr_in_tilde *x = (t_NLMSerr_in_tilde *)pd_new(NLMSerr_in_tilde_class);
t_int i, n_order=39;
t_symbol *w_name;
t_float beta=0.01f;
t_float gammax=0.00001f;
if((argc >= 4) &&
IS_A_FLOAT(argv,0) && //IS_A_FLOAT/SYMBOL from iemlib.h
IS_A_FLOAT(argv,1) &&
IS_A_FLOAT(argv,2) &&
IS_A_SYMBOL(argv,3))
{
n_order = (t_int)atom_getintarg(0, argc, argv);
beta = (t_float)atom_getfloatarg(1, argc, argv);
gammax = (t_float)atom_getfloatarg(2, argc, argv);
w_name = (t_symbol *)atom_getsymbolarg(3, argc, argv);
if(beta < 0.0f)
beta = 0.0f;
if(beta > 2.0f)
beta = 2.0f;
if(gammax < 0.0f)
gammax = 0.0f;
if(gammax > 1.0f)
gammax = 1.0f;
if(n_order < 2)
n_order = 2;
if(n_order > 1111111)
n_order = 1111111;
inlet_new(&x->x_obj, &x->x_obj.ob_pd, &s_signal, &s_signal);
inlet_new(&x->x_obj, &x->x_obj.ob_pd, &s_signal, &s_signal);
outlet_new(&x->x_obj, &s_signal);
x->x_flt_sig_in1 = 0;
x->x_n_order = n_order;
x->x_update = 0;
x->x_beta = beta;
x->x_gamma = gammax;
// 2 times in and one time err_in memory allocation (history)
x->x_ref_filt_in_hist = (t_float *)getbytes(x->x_n_order*sizeof(t_float));
x->x_ref_adapt_in_hist = (t_float *)getbytes(x->x_n_order*sizeof(t_float));
// table-symbols will be linked to their memory in future (dsp_routine)
x->x_w_array_sym_name = gensym(w_name->s_name);
x->x_w_array_mem_beg = (t_float *)0;
x->x_rw_index = 0;
return(x);
}
else
{
post("NLMSerr_in~-ERROR: need 3 float- + 1 symbol-arguments:");
post(" order_of_filter + learnrate_beta + security_value + array_name_taps");
return(0);
}
}
void NLMSerr_in_tilde_setup(void)
{
NLMSerr_in_tilde_class = class_new(gensym("NLMSerr_in~"), (t_newmethod)NLMSerr_in_tilde_new, (t_method)NLMSerr_in_tilde_free,
sizeof(t_NLMSerr_in_tilde), 0, A_GIMME, 0);
CLASS_MAINSIGNALIN(NLMSerr_in_tilde_class, t_NLMSerr_in_tilde, x_flt_sig_in1);
class_addmethod(NLMSerr_in_tilde_class, (t_method)NLMSerr_in_tilde_dsp, gensym("dsp"), 0);
class_addmethod(NLMSerr_in_tilde_class, (t_method)NLMSerr_in_tilde_update, gensym("update"), A_FLOAT, 0); // method: downsampling factor of learning (multiple of 2^N)
class_addmethod(NLMSerr_in_tilde_class, (t_method)NLMSerr_in_tilde_beta, gensym("beta"), A_FLOAT, 0); //method: normalized learning rate
class_addmethod(NLMSerr_in_tilde_class, (t_method)NLMSerr_in_tilde_gamma, gensym("gamma"), A_FLOAT, 0); // method: dithering noise related to signal
}
......@@ -6,11 +6,6 @@ lib iem_adaptfilt written by Markus Noisternig & Thomas Musil
noisternig_AT_iem.at; musil_AT_iem.at
(c) Institute of Electronic Music and Acoustics, Graz Austria 2005 */
#ifdef NT
#pragma warning( disable : 4244 )
#pragma warning( disable : 4305 )
#endif
#include "m_pd.h"
#include "iemlib.h"
......@@ -149,7 +144,7 @@ static t_int *NLMS_tilde_perform(t_int *w)
t_float *w_filt_coeff = x->x_w_array_mem_beg;
t_float my, my_err, sum;
t_float beta = x->x_beta;
t_float gamma = x->x_gamma;
t_float gammax = x->x_gamma;
t_int i, j, update_counter;
t_int update = x->x_update;
t_int ord8=n_order&0xfffffff8;
......@@ -211,7 +206,7 @@ static t_int *NLMS_tilde_perform(t_int *w)
}
for(j=0; j<ord_residual; j++) // residual
sum += read_in_hist[-j] * read_in_hist[-j]; // [-j] only valid for Musil's double buffer structure
sum += gamma * gamma * (float)n_order; // convert gamma corresponding to filter order
sum += gammax * gammax * (float)n_order; // convert gammax corresponding to filter order
my = beta / sum;// calculate mue
......@@ -270,7 +265,7 @@ static void *NLMS_tilde_new(t_symbol *s, t_int argc, t_atom *argv)
t_int i, n_order=39;
t_symbol *w_name;
t_float beta=0.1f;