First ANSI C version of NLMS uploaded which can compile without errors

This commit is contained in:
Friese 2018-04-30 14:38:28 +02:00
parent 30542bacec
commit 982e9edd77
3 changed files with 212 additions and 133 deletions

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@ -2,8 +2,8 @@
// main.c // main.c
// NLMS // NLMS
// //
// Created by Stefan Fiese on 26.04.18. // Created by FBRDNLMS on 26.04.18.
// Copyright © 2018 Stefan Fiese. All rights reserved. // Copyright © 2018 FBRDNLMS. All rights reserved.
// //
#include <stdio.h> #include <stdio.h>
@ -13,7 +13,7 @@
#include <string.h> #include <string.h>
#define M 1000 #define M 1000
#define tracking 40; //Count of weights #define tracking 40 //Count of weights
//static Stack<double> x = new Stack<double>(); //static Stack<double> x = new Stack<double>();
//static Random rnd = new Random(); //static Random rnd = new Random();
//static double[] _x = new double[M]; //static double[] _x = new double[M];
@ -24,182 +24,221 @@ double x[] ={0};
double _x[M] = {0}; double _x[M] = {0};
double w [M][M]={{0},{0}}; double w [M][M]={{0},{0}};
char filename(void);
void fileName(char *name_suffix);
double r2(void);
double rnd(void);
double sum_array(double x[], int length); double sum_array(double x[], int length);
void direkterVorgaenger(void); void direkterVorgaenger(void);
void lokalerMittelWert(void); void lokalerMittelWert(void);
double r2()
{
return((rand() % 10000) / 10000.0);
}
int rnd()
{
double u;
u = r2();
return u;
}
int main(int argc, char **argv ) { int main(int argc, char **argv ) {
//init test_array, fill in weights by random
int i = 0; int i = 0;
for (i = 0; i < M; i++) { for (i = 0; i < M; i++) {
_x[i] += ((255.0 / M) * i); _x[i] += ((255.0 / M) * i);
for (int k = 1; k < M; k++) for (int k = 1; k < M; k++)
{ {
w[k][i] = rnd(); w[k][i] = rnd();
//Console.WriteLine(String.Format("Weight: {0}", w[k, i]));
} }
} }
// save plain test_array before math magic happened
char weightsBefore [] = "_weights.txt";
fileName(&weightsBefore);
FILE *fp0 = fopen(weightsBefore,"wb+");
for (i = 0; i < tracking; i++){ for (i = 0; i < tracking; i++){
for (int k = 1; k < tracking; k++) for ( int k = 1; k < tracking; k++ ){
{ fprintf(fp0, "[%f][%f] %.2f\n", k, i, w[k][i]);
const char *name = fileName(); }
FILE *fp = fopen(*name,"wb+");
File.AppendAllText("weights.txt",
String.Format("[{0}][{1}] {2}\n", k, i, Math.Round(w[k, i], 2).ToString()),
Encoding.UTF8);
}
} }
fclose(fp0);
// math magic
direkterVorgaenger(); direkterVorgaenger();
// save test_array after math magic happened
char weightsAfter [] = "_weights_after.txt";
fileName(&weightsAfter);
FILE *fp1 = fopen(weightsAfter,"wb+");
for (i = 0; i < tracking; i++) { for (i = 0; i < tracking; i++) {
for (int k = 1; k < tracking; k++) { for (int k = 1; k < tracking; k++) {
File.AppendAllText("weights_after.txt", fprintf(fp1, "[%f][%f] %.2f\n", k,i, w[k][i]);
String.Format("[{0}][{1}] {2}\n", k, i, Math.Round(w[k, i], 2).ToString()), }
Encoding.UTF8);
}
} }
fclose(fp1);
getchar(); getchar();
} }
void lokalerMittelWert()
{
int i;
for (i=1; i < M; i++){
// while (x.Count + 1 < M)
double x_pred = 0.0;
double x_middle = (i > 0) ? sum_array(x,i) / i : 0;
double x_actual = _x[i];
for (int j = 1; j < i; j++)
{
x_pred += (w[j, i] * (x[i - j] - x_middle));
}
x_pred += x_middle;
//Console.WriteLine(String.Format("X_sum: {0}", x_middle));
printf("X_pred: {%f}", x_pred);
printf("X_actual: {%f}", x_actual);
double x_error = x_actual - x_pred;
double x_square = 0;
for (int k = 1; k <= i; k++)
{
x_square += pow(x[i - k], 2);
}
for (int l = 1; l < i; l++)
{
w[l, i + 1] = w[l, i] + learnrate * x_error * (x[i - l] / x_square);
}
}
}
static void direkterVorgaenger() /*
{
double x_error[M] = {0}; ===================================
lokalerMittelwert()
Variant (1/3),
substract local mean
===================================
*/
void lokalerMittelWert() {
double xError[M]; // includes e(n)
memset(xError, 0, M);// initialize xError-array with Zero
int xCount = 0; // runtime var
int i; int i;
for(i = 0; i < M; i++)
//while (x.Count + 1 < M)
{ for (xCount = 1; xCount < M; xCount++){ // x_cout can not be zero
double x_pred = 0.0;
//double[] x_array = _x; //double xPartArray[xCount]; //includes all values at the size of runtime var
double x_actual = _x[i + 1];
if (x.Count > 0) double xMean = (xCount > 0) ? ( sum_array(_x, xCount) / xCount) : 0;
{
for (int j = 1; j < i; j++) double xPredicted = 0.0;
{ double xActual = _x[xCount + 1];
x_pred += (w[j, i] * (_x[i - j] - _x[i - j - 1]));
} for ( i = 1; i < xCount; i++ ){ //get predicted value
x_pred += x[i - 1]; xPredicted += (w[i][xCount] * (_x[xCount - i] - xMean)) ;
}
//Console.WriteLine(String.Format("X_sum: {0}", x_middle));
xPredicted += xMean;
//Console.WriteLine(String.Format("X_pred: {0}", x_pred)); xError [xCount] = xActual - xPredicted;
File.AppendAllText("direkterVorgaenger.txt",
String.Format("{0}. X_pred {1}\n",x.Count, x_pred), double xSquared = 0.0;
Encoding.UTF8);
//Console.WriteLine(String.Format("X_actual: {0}", x_actual)); for ( i = 1; i < xCount; i++ ){ //get x squared
File.AppendAllText("direkterVorgaenger.txt", xSquared =+ pow(_x[xCount-i],2);
String.Format("{0}. X_actual {1}\n", x.Count, x_actual),
Encoding.UTF8);
x_error[x.Count] = x_actual - x_pred;
//Console.WriteLine(String.Format("X_error: {0}", x_error));
File.AppendAllText("direkterVorgaenger.txt",
String.Format("{0}. X_error {1}\n\n", x.Count, x_error),
Encoding.UTF8);
double x_square = 0;
for (int k = 1; k < i; k++)
{
x_square += pow(_x[i - k] - _x[i - k - 1], 2);
}
//Console.WriteLine(String.Format("X_square: {0}", x_square));
//File.AppendAllText("direkterVorgaenger.txt",
// String.Format("{0}. X_square {1}\n", x.Count, x_square),
// Encoding.UTF8);
//File.AppendAllText("x_array.txt",
// String.Format("{0}. X_array {1}\n", x.Count, x_array[x.Count - 1]),
// Encoding.UTF8);
for (int l = 1; l < i; l++)
{
w[l, i + 1] = w[l, i] + learnrate * x_error[i] * ((_x[i - l] - x_array[i - l - 1]) / x_square);
}
} }
for ( i - 1; i < xCount; i++ ){ //update weights
w[i][xCount+1] = w[i][xCount] + learnrate * xError[xCount] * (_x[xCount - i] / xSquared);
}
} }
int x_error_array_length = sizeof(error_array_length)/sizeof(error_array_length[0])
double mittel = sum_array(x_error, x_error_array_length) / x_error_array_length; int xErrorLength = sizeof(xError) / sizeof(xError[0]);
double varianz = 0.0; double mean = sum_array(xError, xErrorLength) / M;
for (i = 0; i <= x_error_array_length; i++) double deviation = 0.0;
//foreach(double x_e in x_error)
{ // Mean square
varianz += pow(x_e - mittel, 2); for( i = 0; i < M-1; i++ ){
deviation += pow( xError[i], 2 );
} }
varianz /= x_error_array_length; deviation /= xErrorLength;
File.AppendAllText("ergebnisse.txt",
String.Format("Quadratische Varianz(x_error): {0}\n Mittelwert(x_error): {1}\n\n", varianz, mittel),
Encoding.UTF8); // write in file
char results [] = "_results.txt";
fileName(&results);
FILE *fp2 = fopen(results, "wb+");
fprintf(fp2, "quadr. Varianz(x_error): {%f}\nMittelwert:(x_error): {%f}\n\n", deviation, mean);
fclose(fp2);
} }
char fileName(char *fname){ /*
===================================
direkterVorgaenger()
Variant (2/3),
substract direct predecessor
===================================
*/
void direkterVorgaenger() {
double xError [M];
int xCount = 0, i;
// File handling
char direkterVorgaenger [] = "_direkterVorgaenger.txt";
fileName(&direkterVorgaenger);
FILE *fp3 = fopen(direkterVorgaenger, "wb+");
for ( xCount = 1; xCount < M; xCount++ ){
double xPredicted = 0.0;
double xActual = _x[xCount+1];
for ( i = 1; i < xCount; i++ ){
xPredicted += ( w[i][xCount] * ( _x[xCount - i] - _x[xCount - i - 1]));
}
xPredicted += _x[xCount-1];
xError[xCount] = xActual - xPredicted;
fprintf(fp3, "{%d}.\txPredicted{%f}\txActual{%f}\txError{%f}\n", xCount, xPredicted, xActual, xError[xCount]);
//get x squared
double xSquared = 0;
for ( i = 1; i < xCount; i++ ){
xSquared += pow( _x[xCount - i] - _x[xCount - i - 1], 2); // substract direct predecessor
}
for ( i = 1; x < xCount; i++){
w[i][xCount+1] = w[i][xCount] + learnrate * xError[xCount] * ( ( _x[xCount - i - 1] ) / xSquared );
}
}
int xErrorLength = sizeof(xError) / sizeof(xError[0]);
double mean = sum_array(xError, xErrorLength) / xErrorLength;
double deviation = 0.0;
for ( i = 0; i < xErrorLength -1; i++ ){
deviation += pow( xError[i] - mean, 2);
}
fprintf(fp3, "{%d}.\tLeast Mean Squared{%f}\tMean{%f}\n\n", xCount, deviation, mean);
fclose(fp3);
}
/*
===================================
fileName()
generates filename with date for
logging purposes
===================================
*/
void fileName(char *name_suffix){
//filename //filename
char date[34]; char date[34];
//char name[13] = "_results.txt"; //char name[13] = "_results.txt";
time_t now; time_t now;
now = time(NULL); now = time(NULL);
strftime(date, 20, "%Y-%m-%d_%H_%M_%S", localtime(&now)); strftime(date, 20, "%Y-%m-%d_%H_%M_%S", localtime(&now));
strcpy(date,*fname); strcpy(date, *name_suffix);
//return &date[0]; //return &date[0];
return date; return;
} }
/* /*
=================================== ===================================
@ -210,12 +249,13 @@ char fileName(char *fname){
sum of all elements in x sum of all elements in x
within a defined length within a defined length
==================================== ===================================
*/ */
double sum_array(double x[], int length){ double sum_array(double x[], int length){
//int length = 0; //int length = 0;
int i = 0;
double sum = 0.0; double sum = 0.0;
//length = sizeof(x)/sizeof(x[0]); //length = sizeof(x)/sizeof(x[0]);
for (i=0; i< length; i++){ for (i=0; i< length; i++){
@ -223,3 +263,42 @@ double sum_array(double x[], int length){
} }
return sum; return sum;
} }
/*
===================================
r2()
returns a double value between
0 and 1
===================================
*/
double r2()
{
return((rand() % 10000) / 10000.0);
}
/*
===================================
int rnd()
fills a double variable with
random value and returns it
===================================
*/
double rnd()
{
double u;
u = r2();
return u;
}

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