error as could not open source file malloc.h file

Priyanka Pawar

Respected Sir/Madam,

I have made all the settings correctly in CCS to build the project. In my C program I have used dynamic memory allocation, using calloc() function. But after building the project it is showing an error as "could not open source file malloc.h file". I have added malloc.h file in project folder still error has not been removed. Is DSP6713 does not support dynamic memory allocation? If yes How to do it? Is there any another method..?

Plz, reply as soon as possible.

Thank you in advance for your reply...

over 10 years ago

0 Titusrathinaraj Stalin over 10 years ago

TI__Guru** 116100 points

Hi Priyanka,

No, it will support dynamic memory allocation.

Have you added the "#include "stdlib.h" in your code ?

0 Titusrathinaraj Stalin over 10 years ago

TI__Guru** 116100 points

Hi Priyanka,
I can reproduce your problem with hello world code and able to succeed with adding the "stdlib.h" file.
If it not solve the problem, please re-open the post.
Thank you.

0 Priyanka Pawar over 10 years ago in reply to Titusrathinaraj Stalin

Prodigy 90 points

Thank you for your reply. I have added stdlib.h and removed the malloc.h.

But it showing the errors as shown in the following screenshot.

In my code i am passing values in arrays using pointer (i.e. by passing base address), so i am not getting why it is showing float (*)[32] is incompatible ...

Please help to remove these errors. what I have to do changes to remove these errors...?

0 Titusrathinaraj Stalin over 10 years ago in reply to Priyanka Pawar

TI__Guru** 116100 points

Please attach the screen shot.

0 Priyanka Pawar over 10 years ago in reply to Titusrathinaraj Stalin

Prodigy 90 points

Screenshot of errors..rtfThank you for your reply. I have added stdlib.h and removed the malloc.h.

But it showing the errors as shown in the following screenshot.

In my code i am passing values in arrays using pointer (i.e. by passing base address), so i am not getting why it is showing float (*)[32] is incompatible ...

Please help to remove these errors. what I have to do changes to remove these errors...?

0 Priyanka Pawar over 10 years ago in reply to Priyanka Pawar

Prodigy 90 points

I have added stdlib.h and removed the malloc.h.

But now it is4846.Screenshot of errors..rtf showing the errors as shown in the following attached screenshot.

In my code i am passing values in arrays using pointer (i.e. by passing base address), so i am not getting why it is showing float (*)[32] is incompatible ...

Please help to remove these errors. what I have to do changes to remove these errors...? It is a part of my thesis, so please help as early as possible...since without implementing on DSP6713 I am unable to go further...

Thanking you..

0 Titusrathinaraj Stalin over 10 years ago in reply to Priyanka Pawar

TI__Guru** 116100 points

Provide the line of code which cause the error.

Ex:
You declared and used like "float (*)[1024]"

0 Priyanka Pawar over 10 years ago in reply to Titusrathinaraj Stalin

Prodigy 90 points

Here I am attaching the file naming "awc" consisting of line of code which causes the errors, and also the screenshot of errors.

Please provide the solution earliest

Fullscreen awc.txt Download

#include<stdio.h>
#include<math.h>
#include<stdlib.h>
//#include<malloc.h>

float* convolution_HPF(float *, float *, int, int);  //Prototype
float* convolution_LPF(float *, float *, int, int);  //Prototype 
float* downsample(float *, int);                       //Prototype 
float mean_abs(float *, int);                          //Prototype 

#define L 16  //Length of input data
#define N floor(log (L)/log (2))  // levels

//coefficients 
static float LPF_COEF[32] = {0.0031892209253436892,
    0.03490771432362905,
    0.1650642834886438,
    0.43031272284545874,
    0.6373563320829833,
    0.44029025688580486,
    -0.08975108940236352,
    -0.3270633105274758,
    -0.02791820813292813,
    0.21119069394696974,
    0.027340263752899923,
    -0.13238830556335474,
    -0.006239722752156254,
    0.07592423604445779,
    -0.007588974368642594,
    -0.036888397691556774,
    0.010297659641009963,
    0.013993768859843242,
    -0.006990014563390751,
    -0.0036442796214883506,
    0.00312802338120381,
    0.00040789698084934395,
    -0.0009410217493585433,
    0.00011424152003843815,
    0.00017478724522506327,
    -6.103596621404321e-05,
    -1.394566898819319e-05,
    1.133660866126152e-05,
    -1.0435713423102517e-06,
    -7.363656785441815e-07,
    2.3087840868545578e-07,
    -2.1093396300980412e-08};

static float HPF_COEF[32] = {-2.1093396300980412e-08,
    -2.3087840868545578e-07,
    -7.363656785441815e-07,
    1.0435713423102517e-06,
    1.133660866126152e-05,
    1.394566898819319e-05,
    -6.103596621404321e-05,
    -0.00017478724522506327,
    0.00011424152003843815,
    0.0009410217493585433,
    0.00040789698084934395,
    -0.00312802338120381,
    -0.0036442796214883506,
    0.006990014563390751,
    0.013993768859843242,
    -0.010297659641009963,
    -0.036888397691556774,
    0.007588974368642594,
    0.07592423604445779,
    0.006239722752156254,
    -0.13238830556335474,
    -0.027340263752899923,
    0.21119069394696974,
    0.02791820813292813,
    -0.3270633105274758,
    0.08975108940236352,
    0.44029025688580486,
    -0.6373563320829833,
    0.43031272284545874,
    -0.1650642834886438,
    0.03490771432362905,
    -0.0031892209253436892};

main()
{
	float data[L]={-0.1114,
   -0.2036,
    0.0458,
   -0.0011,
    0.0131,
    0.0536,
   -0.0398,
   -0.0798,
   -0.0663,
   -0.0776,
   -0.1351,
   -0.0293,
    0.0932,
   -0.0145,
   -0.0348,
    0.0047};
	float *ccout_HPF, *ccout_LPF, *dsout_HPF, *dsout_LPF, *temp1, *temp2, mean[5], slope;
	int i, LENGTH, N_1, k=0, r, l=1, prv_LENGTH;

	N_1 = (int) N;
	printf("N=%d\n", N_1);

	//1st-level
	r=pow(2,k);
	LENGTH = L/r;    //Length of output sequence 
	if(L<32)
		LENGTH = 32;
	printf("%d\n", LENGTH);

	ccout_HPF = (float *) calloc(sizeof(float), LENGTH);        //ptr to Array storing values of convolution with HPF
	dsout_HPF = (float *) calloc(sizeof(float), (LENGTH/2));   //ptr to Array storing values of downsample output
	ccout_LPF = (float *) calloc(sizeof(float), LENGTH);        //ptr to Array storing values of convolution with LPF
	dsout_LPF = (float *) calloc(sizeof(float), (LENGTH/2));   //ptr to Array storing values of downsample output


	printf("%dst Convolution output with HPF: \n", k+1);
	ccout_HPF = convolution_HPF(&data, &HPF_COEF, L/r, 32);
	for(i=0; i<LENGTH; i++)
		printf("y[%d] = %f\n", i, *(ccout_HPF+i));

	printf("%dst Downsampled output: \n", k+1);
	dsout_HPF = downsample(ccout_HPF, LENGTH);
	//for(i=0; i<LENGTH/2; i++)
		//printf("y[%d] = %f\n", i, *(dsout_HPF+i));

	mean[0] = mean_abs(dsout_HPF, LENGTH/2);
	printf("Mean=%f\n", mean[0]);

	printf("%dst Convolution output with LPF: \n", k+1);
	ccout_LPF = convolution_LPF(&data, &LPF_COEF, L/r, 32);
	//for(i=0; i<LENGTH; i++)
		//printf("y[%d] = %f\n", i, *(ccout_LPF+i));

	printf("%dst Downsampled output: \n", k+1);
	dsout_LPF = downsample(ccout_LPF, LENGTH);
	//for(i=0; i<LENGTH/2; i++)
		//printf("y[%d] = %f\n", i, *(dsout_LPF+i));

	temp1 = (float *) calloc(sizeof(float), LENGTH/2);   
    for(i=0; i<(LENGTH/2); i++)
			*(temp1+i) = *(dsout_LPF+i);
	//for(i=0; i<LENGTH/2; i++)
		//printf("y[%d] = %f\n", i, *(temp1+i));
	prv_LENGTH = LENGTH/2;

	free(ccout_HPF);
	free(ccout_LPF);
	free(dsout_HPF);
	free(dsout_LPF);

	for(k=1, l=1; k<N_1&&l<N_1; k++, l++)                       //2nd to N_1th
	{
		//k=k+1;
		if((LENGTH/2)<=32)
			LENGTH = 32;
		else
		{
			//r=pow(2,k);
		    LENGTH = LENGTH/2;
		}
		printf("%d\n", LENGTH);

		temp2 = (float *) calloc(sizeof(float), LENGTH);
		ccout_HPF = (float *) calloc(sizeof(float), LENGTH);        
		dsout_HPF = (float *) calloc(sizeof(float), (LENGTH/2));   
		ccout_LPF = (float *) calloc(sizeof(float), LENGTH);        
		dsout_LPF = (float *) calloc(sizeof(float), (LENGTH/2));   

		for(i=0; i<prv_LENGTH; i++)
			*(temp2+i) = *(temp1+i);
		for(i=25; i<LENGTH; i++)
			*(temp2+i) = 0;

		printf("%dth Convolution output with HPF: \n", k+1);
		ccout_HPF = convolution_HPF(temp2, &HPF_COEF, LENGTH, 32);
		//for(i=0; i<LENGTH; i++)
			//printf("y[%d] = %f\n", i, *(ccout_HPF+i));

		printf("%dth Downsampled output: \n", k+1);
		dsout_HPF = downsample(ccout_HPF, LENGTH);
		//for(i=0; i<LENGTH/2; i++)
			//printf("y[%d] = %f\n", i, *(dsout_HPF+i));

		mean[l] = mean_abs(dsout_HPF, LENGTH/2);
		printf("Mean=%f\n", mean[l]);

		printf("%dth Convolution output with LPF: \n", k+1);
		ccout_LPF = convolution_LPF(temp2, &LPF_COEF, LENGTH, 32);
		//for(i=0; i<LENGTH; i++)
			//printf("y[%d] = %f\n", i, *(ccout_LPF+i));

		printf("%dth Downsampled output: \n", k+1);
		dsout_LPF = downsample(ccout_LPF, LENGTH);
		//for(i=0; i<LENGTH/2; i++)
			//printf("y[%d] = %f\n", i, *(dsout_LPF+i));

		for(i=0; i<LENGTH/2; i++)
				*(temp1+i) = *(dsout_LPF+i);
		prv_LENGTH = LENGTH/2;

		//printf("\n");
		//for(i=0; i<LENGTH/2; i++)
			//printf("y[%d] = %f\n", i, *(temp1+i));

		free(ccout_HPF);
		free(ccout_LPF);
		free(dsout_HPF);
		free(dsout_LPF);
		free(temp2);

	}

	for(i=LENGTH/2; i<L; i++)
		*(temp1+i) = 0;
	mean[l] = mean_abs(temp1, LENGTH/2);
		printf("Mean=%f\n", mean[l]);



	for(i=0; i<=N; i++)
		printf("Mean = %f\t", mean[i]);

	slope = (log10(mean[4])-log10(mean[0]))/(log10(16.0)-log10(1.0));

	printf("Slope = %f\n", slope);
	printf("Slope = H + 0.5,\tor H=1-Beta/2 \t H = %f\n", 1-(slope/2));

	free(temp1);

}

float *convolution_HPF(float *x, float *h, int n, int m)
{
	float *y, *a, *x2;
	int i, j, k;

	if(n-m !=0)
	{
		if(n>m)
		{
			for(i=m; i<n; i++)
			{
				*(h+i) = 0;
				m = n;
			}
		}
		else
		{
			for(i=n; i<m; i++)
			{
				*(x+i) = 0;
				n = m;
			}
		}
	}

	y = (float *)calloc(sizeof(float), (n));
	a = (float *)calloc(sizeof(float), (n));
	x2 = (float *)calloc(sizeof(float), (n));


	*(y+0) = 0;
	*(a+0) = *(h+0);

	for(j=1;j<n;j++)            
		*(a+j) = *(h+(n-j));

    
    for(i=0;i<n;i++)
		*(y+0) = *(y+0) + (*(x+i) * (*(a+i)));

	for(k=1;k<n;k++)
	{
		*(y+k) = 0;                    

		for(j=1;j<n;j++)
					*(x2+j)=*(a+(j-1));
					*(x2+0)=*(a+(n-1));
		for(i=0;i<n;i++)
		{
					*(a+i)=*(x2+i);
					*(y+k) = *(y+k) + (*(x+i)*(*(x2+i)));
		}
    }

	return y;

	free(y);
}

float *convolution_LPF(float *x, float *h, int n, int m)
{
	float *y, *a, *x2;
	int i, j, k;

	if(n-m !=0)
	{
		if(n>m)
		{
			for(i=m; i<n; i++)
			{
				*(h+i) = 0;
				m = n;
			}
		}
		else
		{
			for(i=n; i<m; i++)
			{
				*(x+i) = 0;
				n = m;
			}
		}
	}

	y = (float *)calloc(sizeof(float), (n));
	a = (float *)calloc(sizeof(float), (n));
	x2 = (float *)calloc(sizeof(float), (n));


	*(y+0) = 0;
	*(a+0) = *(h+0);
	
	for(j=1;j<n;j++)            
		*(a+j) = *(h+(n-j));

    /*Circular convolution*/
    for(i=0;i<n;i++)
		*(y+0) = *(y+0) + (*(x+i) * (*(a+i)));

	for(k=1;k<n;k++)
	{
		*(y+k) = 0;                    

		for(j=1;j<n;j++)
					*(x2+j)=*(a+(j-1));
					*(x2+0)=*(a+(n-1));
		for(i=0;i<n;i++)
		{
					*(a+i)=*(x2+i);
					*(y+k) = *(y+k) + (*(x+i)*(*(x2+i)));
		}
    }

	return y;

	free(y);

}

float * downsample(float *p, int len)
{
	int i, j;
	//float p1[1];
	float *ds;

	ds = (float *) malloc(sizeof(float)*(len/2));

	for(i=0,j=0; i<len/2; i++,j++)
		*(ds+i) = *(p+i+j);

	return ds;

	free(ds);
}

float mean_abs(float *p, int length)
{
	int i=0;
	float sum=0, mean;

	for(i=0; i<length; i++)
	{
		if(*(p+i) >= 0)
			sum = sum + (*(p+i));
		else
			sum = sum +(*(p+i)*(-1));
	}

	mean = (float) sum/length;

	return mean;
}

Screenshot of awc errors.docx to solve the problem.

Thank you...

0 Titusrathinaraj Stalin over 10 years ago in reply to Priyanka Pawar

TI__Guru** 116100 points

Try to change the code like following.

ccout_LPF = convolution_LPF(data, LPF_COEF, L/r, 32);
ccout_HPF = (float * ) convolution_HPF(data, HPF_COEF, L/r, 32);
ccout_HPF = convolution_HPF(temp2, HPF_COEF, LENGTH, 32);
ccout_LPF = convolution_LPF(temp2, LPF_COEF, LENGTH, 32);

0 Priyanka Pawar over 10 years ago in reply to Titusrathinaraj Stalin

Prodigy 90 points

Thank you... I have made changes and it has removed the errors...

But now I am getting trouble for implementing it on DSP6713.

I am getting run-time Memory map error... could you please see the attached code and tell me why it is happening, what i have to do to successfully implement on DSP

Fullscreen awc1.c.txt Download

#include<stdio.h>
#include<math.h>
#include<stdlib.h>
//#include<malloc.h>

float* convolution_HPF(float *, float *, int, int);  //Prototype for convolution of data with HPF coefficient
float* convolution_LPF(float *, float *, int, int);  //Prototype for convolution of data with LPF coefficient
float* downsample(float *, int);                     //Prototype for downsampling the sequence
float mean_abs(float *, int);                        //Prototype for calculating mean of detail coefficeints at each decomposition stage
float linreg(float [], int);

#define L 201                                       //Length of input data
#define N floor(log10(L)/log10(2))                     //No. of Decomposition levels

//Filter coefficients for Daubechies16 wavelet
static float LPF_COEF[32] = {0.0031892209253436892,
    0.03490771432362905,
    0.1650642834886438,
    0.43031272284545874,
    0.6373563320829833,
    0.44029025688580486,
    -0.08975108940236352,
    -0.3270633105274758,
    -0.02791820813292813,
    0.21119069394696974,
    0.027340263752899923,
    -0.13238830556335474,
    -0.006239722752156254,
    0.07592423604445779,
    -0.007588974368642594,
    -0.036888397691556774,
    0.010297659641009963,
    0.013993768859843242,
    -0.006990014563390751,
    -0.0036442796214883506,
    0.00312802338120381,
    0.00040789698084934395,
    -0.0009410217493585433,
    0.00011424152003843815,
    0.00017478724522506327,
    -6.103596621404321e-05,
    -1.394566898819319e-05,
    1.133660866126152e-05,
    -1.0435713423102517e-06,
    -7.363656785441815e-07,
    2.3087840868545578e-07,
    -2.1093396300980412e-08};

static float HPF_COEF[32] = {-2.1093396300980412e-08,
    -2.3087840868545578e-07,
    -7.363656785441815e-07,
    1.0435713423102517e-06,
    1.133660866126152e-05,
    1.394566898819319e-05,
    -6.103596621404321e-05,
    -0.00017478724522506327,
    0.00011424152003843815,
    0.0009410217493585433,
    0.00040789698084934395,
    -0.00312802338120381,
    -0.0036442796214883506,
    0.006990014563390751,
    0.013993768859843242,
    -0.010297659641009963,
    -0.036888397691556774,
    0.007588974368642594,
    0.07592423604445779,
    0.006239722752156254,
    -0.13238830556335474,
    -0.027340263752899923,
    0.21119069394696974,
    0.02791820813292813,
    -0.3270633105274758,
    0.08975108940236352,
    0.44029025688580486,
    -0.6373563320829833,
    0.43031272284545874,
    -0.1650642834886438,
    0.03490771432362905,
    -0.0031892209253436892};

main()
{
	float data[L]={19,
23,
31,
18,
22,
34,
30,
37,
62,
28,
40,
47,
28,
26,
43,
46,
20,
68,
62,
29,
52,
33,
30,
35,
40,
5,
28,
41,
18,
35,
21,
16,
14,
28,
15,
29,
33,
16,
21,
9,
17,
20,
23,
24,
33,
12,
22,
31,
34,
7,
22,
23,
21,
42,
10,
15,
20,
15,
15,
29,
14,
9,
11,
32,
7,
30,
39,
34,
32,
31,
40,
23,
35,
63,
28,
44,
23,
29,
22,
12,
17,
23,
6,
9,
10,
30,
8,
8,
27,
40,
32,
23,
31,
14,
28,
21,
20,
28,
27,
15,
22,
24,
31,
14,
43,
15,
14,
16,
16,
3,
29,
8,
11,
16,
17,
46,
25,
25,
39,
18,
30,
17,
16,
24,
14,
14,
14,
24,
31,
10,
13,
27,
14,
52,
36,
26,
27,
25,
32,
11,
33,
41,
23,
52,
28,
37,
41,
14,
21,
17,
16,
7,
24,
7,
12,
25,
7,
6,
44,
9,
18,
41,
26,
26,
31,
17,
10,
30,
14,
9,
37,
30,
11,
12,
33,
17,
8,
9,
46,
7,
6,
5,
31,
3,
15,
12,
19,
23,
53,
21,
41,
19,
52,
16,
39,
22,
7,
7,
40,
19,
9};
	float *ccout_HPF, *ccout_LPF, *dsout_HPF, *dsout_LPF, *temp1, *temp2, mean[11], slope;
	int i, LENGTH, N_1, k=0, r, l=1, prv_LENGTH;

	N_1 = (int) N;
	printf("N=%d\n", N_1);

	//1st-level decomposition
	r=pow(2,k);
	LENGTH = L/r;    //Length of output sequence of convolution at each step
	if(L<32)
		LENGTH = 32;
	printf("%d\n", LENGTH);

	ccout_HPF = (float *) calloc(sizeof(float), LENGTH);        //ptr to Array storing values of convolution with HPF
	dsout_HPF = (float *) calloc(sizeof(float), (LENGTH/2));   //ptr to Array storing values of downsample output
	ccout_LPF = (float *) calloc(sizeof(float), LENGTH);        //ptr to Array storing values of convolution with LPF
	dsout_LPF = (float *) calloc(sizeof(float), (LENGTH/2));   //ptr to Array storing values of downsample output


	printf("%dst Convolution output with HPF: \n", k+1);
	ccout_HPF = convolution_HPF(data, HPF_COEF, L/r, 32);
	for(i=0; i<LENGTH; i++)
		printf("y[%d] = %f\n", i, *(ccout_HPF+i));

	printf("%dst Downsampled output: \n", k+1);
	dsout_HPF = downsample(ccout_HPF, LENGTH);
	for(i=0; i<LENGTH/2; i++)
		printf("y[%d] = %f\n", i, *(dsout_HPF+i));

	mean[0] = mean_abs(dsout_HPF, LENGTH/2);
	printf("Mean=%f\n", mean[0]);

	printf("%dst Convolution output with LPF: \n", k+1);
	ccout_LPF = convolution_LPF(data, LPF_COEF, L/r, 32);
	for(i=0; i<LENGTH; i++)
		printf("y[%d] = %f\n", i, *(ccout_LPF+i));

	printf("%dst Downsampled output: \n", k+1);
	dsout_LPF = downsample(ccout_LPF, LENGTH);
	//for(i=0; i<LENGTH/2; i++)
		//printf("y[%d] = %f\n", i, *(dsout_LPF+i));

	temp1 = (float *) calloc(sizeof(float), LENGTH/2);      //pointer to Array storing values of approximation at each step
    for(i=0; i<(LENGTH/2); i++)
			*(temp1+i) = *(dsout_LPF+i);
	//for(i=0; i<LENGTH/2; i++)
		//printf("y[%d] = %f\n", i, *(temp1+i));
	prv_LENGTH = LENGTH/2;

	free(ccout_HPF);
	free(ccout_LPF);
	free(dsout_HPF);
	free(dsout_LPF);
	//End of 1st level decomposition

	for(k=1, l=1; k<N_1&&l<N_1; k++, l++)                           //2nd to N_1th stage decomposition
	{
		//k=k+1;
		if((LENGTH/2)<=32)
			LENGTH = 32;
		else
		{
			//r=pow(2,k);
		    LENGTH = LENGTH/2;
		}
		printf("%d\n", LENGTH);

		temp2 = (float *) calloc(sizeof(float), LENGTH);
		ccout_HPF = (float *) calloc(sizeof(float), LENGTH);        //ptr to Array storing values of convolution with HPF
		dsout_HPF = (float *) calloc(sizeof(float), (LENGTH/2));    //ptr to Array storing values of downsample output
		ccout_LPF = (float *) calloc(sizeof(float), LENGTH);        //ptr to Array storing values of convolution with LPF
		dsout_LPF = (float *) calloc(sizeof(float), (LENGTH/2));   //ptr to Array storing values of downsample output

		for(i=0; i<prv_LENGTH; i++)
			*(temp2+i) = *(temp1+i);
		for(i=25; i<LENGTH; i++)
			*(temp2+i) = 0;

		printf("%dth Convolution output with HPF: \n", k+1);
		ccout_HPF = convolution_HPF(temp2, HPF_COEF, LENGTH, 32);
		//for(i=0; i<LENGTH; i++)
			//printf("y[%d] = %f\n", i, *(ccout_HPF+i));

		printf("%dth Downsampled output: \n", k+1);
		dsout_HPF = downsample(ccout_HPF, LENGTH);
		for(i=0; i<LENGTH/2; i++)
			printf("y[%d] = %f\n", i, *(dsout_HPF+i));

		mean[l] = mean_abs(dsout_HPF, LENGTH/2);
		printf("Mean=%f\n", mean[l]);

		printf("%dth Convolution output with LPF: \n", k+1);
		ccout_LPF = convolution_LPF(temp2, LPF_COEF, LENGTH, 32);
		//for(i=0; i<LENGTH; i++)
			//printf("y[%d] = %f\n", i, *(ccout_LPF+i));

		printf("%dth Downsampled output: \n", k+1);
		dsout_LPF = downsample(ccout_LPF, LENGTH);
		//for(i=0; i<LENGTH/2; i++)
			//printf("y[%d] = %f\n", i, *(dsout_LPF+i));

		for(i=0; i<LENGTH/2; i++)
				*(temp1+i) = *(dsout_LPF+i);
		prv_LENGTH = LENGTH/2;

		//printf("\n");
		//for(i=0; i<LENGTH/2; i++)
			//printf("y[%d] = %f\n", i, *(temp1+i));

		free(ccout_HPF);
		free(ccout_LPF);
		free(dsout_HPF);
		free(dsout_LPF);
		free(temp2);

	}

	for(i=LENGTH/2; i<L; i++)
		*(temp1+i) = 0;
	mean[l] = mean_abs(temp1, LENGTH/2);
		printf("Mean=%f\n", mean[l]);

	for(i=0; i<=N; i++)
		printf("Mean = %f\t", mean[i]);

	slope = linreg(mean, N_1);                                                        //Slope calculation using Linear regression method
	printf("%f\n", slope);
	printf("Slope = H + 0.5,\tor H=1-Beta/2 \t H = %f\n", 1-(slope/2));

	/*slope = (log10(mean[10])-log10(mean[0]))/(log10(1024.0)-log10(1.0));            // Slope and H calculation using simple m = ((y2-y1)/(x2-x1))method

	printf("Slope = %f\n", slope);
	printf("Slope = H + 0.5,\tor H=1-Beta/2 \t H = %f\n", 1-(slope/2));*/

	free(temp1);

}

float *convolution_HPF(float *x, float *h, int n, int m)
{
	float *y, *a, *x2;
	int i, j, k;

	if(n-m !=0)
	{
		if(n>m)
		{
			for(i=m; i<n; i++)
			{
				*(h+i) = 0;
				m = n;
			}
		}
		else
		{
			for(i=n; i<m; i++)
			{
				*(x+i) = 0;
				n = m;
			}
		}
	}

	y = (float *)calloc(sizeof(float), (n));
	a = (float *)calloc(sizeof(float), (n));
	x2 = (float *)calloc(sizeof(float), (n));


	*(y+0) = 0;
	*(a+0) = *(h+0);

	for(j=1;j<n;j++)            /*folding h(n) to h(-n)*/
		*(a+j) = *(h+(n-j));

    /*Circular convolution*/
    for(i=0;i<n;i++)
		*(y+0) = *(y+0) + (*(x+i) * (*(a+i)));

	for(k=1;k<n;k++)
	{
		*(y+k) = 0;                    /*circular shift*/

		for(j=1;j<n;j++)
					*(x2+j)=*(a+(j-1));
					*(x2+0)=*(a+(n-1));
		for(i=0;i<n;i++)
		{
					*(a+i)=*(x2+i);
					*(y+k) = *(y+k) + (*(x+i)*(*(x2+i)));
		}
    }

	return y;

	free(y);
	free(a);
	free(x2);
}

float *convolution_LPF(float *x, float *h, int n, int m)
{
	float *y, *a, *x2;
	int i, j, k;

	if(n-m !=0)
	{
		if(n>m)
		{
			for(i=m; i<n; i++)
			{
				*(h+i) = 0;
				m = n;
			}
		}
		else
		{
			for(i=n; i<m; i++)
			{
				*(x+i) = 0;
				n = m;
			}
		}
	}

	y = (float *)calloc(sizeof(float), (n));
	a = (float *)calloc(sizeof(float), (n));
	x2 = (float *)calloc(sizeof(float), (n));


	*(y+0) = 0;
	*(a+0) = *(h+0);

	for(j=1;j<n;j++)            /*folding h(n) to h(-n)*/
		*(a+j) = *(h+(n-j));

    /*Circular convolution*/
    for(i=0;i<n;i++)
		*(y+0) = *(y+0) + (*(x+i) * (*(a+i)));

	for(k=1;k<n;k++)
	{
		*(y+k) = 0;                    /*circular shift*/

		for(j=1;j<n;j++)
					*(x2+j)=*(a+(j-1));
					*(x2+0)=*(a+(n-1));
		for(i=0;i<n;i++)
		{
					*(a+i)=*(x2+i);
					*(y+k) = *(y+k) + (*(x+i)*(*(x2+i)));
		}
    }

	return y;

	free(y);
	free(a);
	free(x2);

}

float * downsample(float *p, int len)
{
	int i, j;
	//float p1[1];
	float *ds;

	ds = (float *) malloc(sizeof(float)*(len/2));

	for(i=0,j=0; i<len/2; i++,j++)
		*(ds+i) = *(p+i+j);

	return ds;

	free(ds);
}

float mean_abs(float *p, int length)
{
	int i=0;
	float sum=0, mean;

	for(i=0; i<length; i++)
	{
		if(*(p+i) >= 0)
			sum = sum + (*(p+i));
		else
			sum = sum +(*(p+i)*(-1));
	}

	mean = (float) sum/length;

	return mean;
}

float linreg(float p[], int N_1)
{
	int i;
	float sum_x=0, sum_y=0, sum_xy=0, sum_x2=0, m, temp=0;

	for(i=0; i<=N_1; i++)
		sum_x = sum_x + log10(pow(2,i));
	//printf("%f\n", sum_x);

	for(i=0; i<=N_1; i++)
		sum_x2 = sum_x2 + (log10(pow(2,i))*log10(pow(2,i)));
	//printf("%f\n", sum_x2);

	for(i=0; i<=N_1; i++)
	{
		temp = p[i];
		if(temp>0 || temp<0)
			sum_y = sum_y + log10 (temp);
	}
	//printf("%f\n", sum_y);

	for(i=0; i<=N_1; i++)
	{
		temp = p[i];
		if(temp>0 ||temp<0)
			sum_xy = sum_xy + (log10(pow(2,i)) * log10(temp));
	}
	//printf("%f\n", sum_xy);

	m = ((N_1+1)*sum_xy - sum_x*sum_y) / ((N_1+1)*sum_x2 - pow(sum_x, 2));

	printf("Slope = %f\t H = 1-(slope)/2 = %f\n", m, 1-(m/2));

	return m;
}

6713.. I have done all settings correctly, in target configurations I have chosen Texas instrument simulator, and C6713, little endian mode.

I have checked by step by step debugging, when it is returning from function convolution_HPF It is not printing the output in main... and goes the control to the first line after declaration N_1 = (int) N; in main... and shows the run-time error as that program counter is not getting next location and therefore it is again going to N_1 = (int) N; line also some of errors while debugging(not step by step) is "Can't find a source file at "c:\docume~1\win_xp\locals~1\temp\tia672~1\src/exit.c" Locate the file or edit the source lookup path to include its location."

what another path I have to add?

The same program I have done in Visual studio 2010, and it is showing the output H=0.97... Please Help me to solve these problems as early as possible... Since 5 days I am working on these problems, still solution not found.. Please help earlier...

Thank you in advance...

0 Priyanka Pawar over 10 years ago in reply to Priyanka Pawar

Prodigy 90 points

Respected Sir/Madam,

I am Priyanka G. Pawar, Student of Second Year M.tech(Electronics- Digital Systems), in College of Engineering Pune, Maharashtra.

I have joined this support forum to discuss problems that I am facing while implementing my M.tech thesis code on DSP6713 processor. My Guide Mr. Prof. P. W. Wani, and Co-guide Mr. Prof. A. B. Patki from College of Engineering, Pune(Maharashtra) wants to communicate with you regarding this code. I am attaching copy of code that I have mailed to you earlier. Please tell when they can communicate with you.

In my last mail I have told you about getting trouble for implementing it on DSP6713. I am getting run-time Memory map error... could you please see the attached code and tell me why it is happening, what i have to do to successfully implement on DSP. I have done all settings correctly, in target configurations I have chosen Texas instrument simulator, and C6713, little endian mode. I have checked by step by step debugging, when it is returning from function convolution_HPF It is not printing the output in main... and goes the control to the first line after declaration N_1 = (int) N; in main... and shows the run-time error as that program counter is not getting next location and therefore it is again going to N_1 = (int) N; line also some of errors while debugging(not step by step) is "Can't find a source file at "c:\docume~1\win_xp\locals~1\temp\tia672~1\src/exit.c" Locate the file or edit the source lookup path to include its location."

what another path I have to add?

For this I have not get any reply up till now., Please help me to find out solution earlier..

Here i am attaching the code file.

Fullscreen 5861.awc1.c.txt Download

#include<stdio.h>
#include<math.h>
#include<stdlib.h>
//#include<malloc.h>

float* convolution_HPF(float *, float *, int, int);  //Prototype for convolution of data with HPF coefficient
float* convolution_LPF(float *, float *, int, int);  //Prototype for convolution of data with LPF coefficient
float* downsample(float *, int);                     //Prototype for downsampling the sequence
float mean_abs(float *, int);                        //Prototype for calculating mean of detail coefficeints at each decomposition stage
float linreg(float [], int);

#define L 201                                       //Length of input data
#define N floor(log10(L)/log10(2))                     //No. of Decomposition levels

//Filter coefficients for Daubechies16 wavelet
static float LPF_COEF[32] = {0.0031892209253436892,
    0.03490771432362905,
    0.1650642834886438,
    0.43031272284545874,
    0.6373563320829833,
    0.44029025688580486,
    -0.08975108940236352,
    -0.3270633105274758,
    -0.02791820813292813,
    0.21119069394696974,
    0.027340263752899923,
    -0.13238830556335474,
    -0.006239722752156254,
    0.07592423604445779,
    -0.007588974368642594,
    -0.036888397691556774,
    0.010297659641009963,
    0.013993768859843242,
    -0.006990014563390751,
    -0.0036442796214883506,
    0.00312802338120381,
    0.00040789698084934395,
    -0.0009410217493585433,
    0.00011424152003843815,
    0.00017478724522506327,
    -6.103596621404321e-05,
    -1.394566898819319e-05,
    1.133660866126152e-05,
    -1.0435713423102517e-06,
    -7.363656785441815e-07,
    2.3087840868545578e-07,
    -2.1093396300980412e-08};

static float HPF_COEF[32] = {-2.1093396300980412e-08,
    -2.3087840868545578e-07,
    -7.363656785441815e-07,
    1.0435713423102517e-06,
    1.133660866126152e-05,
    1.394566898819319e-05,
    -6.103596621404321e-05,
    -0.00017478724522506327,
    0.00011424152003843815,
    0.0009410217493585433,
    0.00040789698084934395,
    -0.00312802338120381,
    -0.0036442796214883506,
    0.006990014563390751,
    0.013993768859843242,
    -0.010297659641009963,
    -0.036888397691556774,
    0.007588974368642594,
    0.07592423604445779,
    0.006239722752156254,
    -0.13238830556335474,
    -0.027340263752899923,
    0.21119069394696974,
    0.02791820813292813,
    -0.3270633105274758,
    0.08975108940236352,
    0.44029025688580486,
    -0.6373563320829833,
    0.43031272284545874,
    -0.1650642834886438,
    0.03490771432362905,
    -0.0031892209253436892};

main()
{
	float data[L]={19,
23,
31,
18,
22,
34,
30,
37,
62,
28,
40,
47,
28,
26,
43,
46,
20,
68,
62,
29,
52,
33,
30,
35,
40,
5,
28,
41,
18,
35,
21,
16,
14,
28,
15,
29,
33,
16,
21,
9,
17,
20,
23,
24,
33,
12,
22,
31,
34,
7,
22,
23,
21,
42,
10,
15,
20,
15,
15,
29,
14,
9,
11,
32,
7,
30,
39,
34,
32,
31,
40,
23,
35,
63,
28,
44,
23,
29,
22,
12,
17,
23,
6,
9,
10,
30,
8,
8,
27,
40,
32,
23,
31,
14,
28,
21,
20,
28,
27,
15,
22,
24,
31,
14,
43,
15,
14,
16,
16,
3,
29,
8,
11,
16,
17,
46,
25,
25,
39,
18,
30,
17,
16,
24,
14,
14,
14,
24,
31,
10,
13,
27,
14,
52,
36,
26,
27,
25,
32,
11,
33,
41,
23,
52,
28,
37,
41,
14,
21,
17,
16,
7,
24,
7,
12,
25,
7,
6,
44,
9,
18,
41,
26,
26,
31,
17,
10,
30,
14,
9,
37,
30,
11,
12,
33,
17,
8,
9,
46,
7,
6,
5,
31,
3,
15,
12,
19,
23,
53,
21,
41,
19,
52,
16,
39,
22,
7,
7,
40,
19,
9};
	float *ccout_HPF, *ccout_LPF, *dsout_HPF, *dsout_LPF, *temp1, *temp2, mean[11], slope;
	int i, LENGTH, N_1, k=0, r, l=1, prv_LENGTH;

	N_1 = (int) N;
	printf("N=%d\n", N_1);

	//1st-level decomposition
	r=pow(2,k);
	LENGTH = L/r;    //Length of output sequence of convolution at each step
	if(L<32)
		LENGTH = 32;
	printf("%d\n", LENGTH);

	ccout_HPF = (float *) calloc(sizeof(float), LENGTH);        //ptr to Array storing values of convolution with HPF
	dsout_HPF = (float *) calloc(sizeof(float), (LENGTH/2));   //ptr to Array storing values of downsample output
	ccout_LPF = (float *) calloc(sizeof(float), LENGTH);        //ptr to Array storing values of convolution with LPF
	dsout_LPF = (float *) calloc(sizeof(float), (LENGTH/2));   //ptr to Array storing values of downsample output


	printf("%dst Convolution output with HPF: \n", k+1);
	ccout_HPF = convolution_HPF(data, HPF_COEF, L/r, 32);
	for(i=0; i<LENGTH; i++)
		printf("y[%d] = %f\n", i, *(ccout_HPF+i));

	printf("%dst Downsampled output: \n", k+1);
	dsout_HPF = downsample(ccout_HPF, LENGTH);
	for(i=0; i<LENGTH/2; i++)
		printf("y[%d] = %f\n", i, *(dsout_HPF+i));

	mean[0] = mean_abs(dsout_HPF, LENGTH/2);
	printf("Mean=%f\n", mean[0]);

	printf("%dst Convolution output with LPF: \n", k+1);
	ccout_LPF = convolution_LPF(data, LPF_COEF, L/r, 32);
	for(i=0; i<LENGTH; i++)
		printf("y[%d] = %f\n", i, *(ccout_LPF+i));

	printf("%dst Downsampled output: \n", k+1);
	dsout_LPF = downsample(ccout_LPF, LENGTH);
	//for(i=0; i<LENGTH/2; i++)
		//printf("y[%d] = %f\n", i, *(dsout_LPF+i));

	temp1 = (float *) calloc(sizeof(float), LENGTH/2);      //pointer to Array storing values of approximation at each step
    for(i=0; i<(LENGTH/2); i++)
			*(temp1+i) = *(dsout_LPF+i);
	//for(i=0; i<LENGTH/2; i++)
		//printf("y[%d] = %f\n", i, *(temp1+i));
	prv_LENGTH = LENGTH/2;

	free(ccout_HPF);
	free(ccout_LPF);
	free(dsout_HPF);
	free(dsout_LPF);
	//End of 1st level decomposition

	for(k=1, l=1; k<N_1&&l<N_1; k++, l++)                           //2nd to N_1th stage decomposition
	{
		//k=k+1;
		if((LENGTH/2)<=32)
			LENGTH = 32;
		else
		{
			//r=pow(2,k);
		    LENGTH = LENGTH/2;
		}
		printf("%d\n", LENGTH);

		temp2 = (float *) calloc(sizeof(float), LENGTH);
		ccout_HPF = (float *) calloc(sizeof(float), LENGTH);        //ptr to Array storing values of convolution with HPF
		dsout_HPF = (float *) calloc(sizeof(float), (LENGTH/2));    //ptr to Array storing values of downsample output
		ccout_LPF = (float *) calloc(sizeof(float), LENGTH);        //ptr to Array storing values of convolution with LPF
		dsout_LPF = (float *) calloc(sizeof(float), (LENGTH/2));   //ptr to Array storing values of downsample output

		for(i=0; i<prv_LENGTH; i++)
			*(temp2+i) = *(temp1+i);
		for(i=25; i<LENGTH; i++)
			*(temp2+i) = 0;

		printf("%dth Convolution output with HPF: \n", k+1);
		ccout_HPF = convolution_HPF(temp2, HPF_COEF, LENGTH, 32);
		//for(i=0; i<LENGTH; i++)
			//printf("y[%d] = %f\n", i, *(ccout_HPF+i));

		printf("%dth Downsampled output: \n", k+1);
		dsout_HPF = downsample(ccout_HPF, LENGTH);
		for(i=0; i<LENGTH/2; i++)
			printf("y[%d] = %f\n", i, *(dsout_HPF+i));

		mean[l] = mean_abs(dsout_HPF, LENGTH/2);
		printf("Mean=%f\n", mean[l]);

		printf("%dth Convolution output with LPF: \n", k+1);
		ccout_LPF = convolution_LPF(temp2, LPF_COEF, LENGTH, 32);
		//for(i=0; i<LENGTH; i++)
			//printf("y[%d] = %f\n", i, *(ccout_LPF+i));

		printf("%dth Downsampled output: \n", k+1);
		dsout_LPF = downsample(ccout_LPF, LENGTH);
		//for(i=0; i<LENGTH/2; i++)
			//printf("y[%d] = %f\n", i, *(dsout_LPF+i));

		for(i=0; i<LENGTH/2; i++)
				*(temp1+i) = *(dsout_LPF+i);
		prv_LENGTH = LENGTH/2;

		//printf("\n");
		//for(i=0; i<LENGTH/2; i++)
			//printf("y[%d] = %f\n", i, *(temp1+i));

		free(ccout_HPF);
		free(ccout_LPF);
		free(dsout_HPF);
		free(dsout_LPF);
		free(temp2);

	}

	for(i=LENGTH/2; i<L; i++)
		*(temp1+i) = 0;
	mean[l] = mean_abs(temp1, LENGTH/2);
		printf("Mean=%f\n", mean[l]);

	for(i=0; i<=N; i++)
		printf("Mean = %f\t", mean[i]);

	slope = linreg(mean, N_1);                                                        //Slope calculation using Linear regression method
	printf("%f\n", slope);
	printf("Slope = H + 0.5,\tor H=1-Beta/2 \t H = %f\n", 1-(slope/2));

	/*slope = (log10(mean[10])-log10(mean[0]))/(log10(1024.0)-log10(1.0));            // Slope and H calculation using simple m = ((y2-y1)/(x2-x1))method

	printf("Slope = %f\n", slope);
	printf("Slope = H + 0.5,\tor H=1-Beta/2 \t H = %f\n", 1-(slope/2));*/

	free(temp1);

}

float *convolution_HPF(float *x, float *h, int n, int m)
{
	float *y, *a, *x2;
	int i, j, k;

	if(n-m !=0)
	{
		if(n>m)
		{
			for(i=m; i<n; i++)
			{
				*(h+i) = 0;
				m = n;
			}
		}
		else
		{
			for(i=n; i<m; i++)
			{
				*(x+i) = 0;
				n = m;
			}
		}
	}

	y = (float *)calloc(sizeof(float), (n));
	a = (float *)calloc(sizeof(float), (n));
	x2 = (float *)calloc(sizeof(float), (n));


	*(y+0) = 0;
	*(a+0) = *(h+0);

	for(j=1;j<n;j++)            /*folding h(n) to h(-n)*/
		*(a+j) = *(h+(n-j));

    /*Circular convolution*/
    for(i=0;i<n;i++)
		*(y+0) = *(y+0) + (*(x+i) * (*(a+i)));

	for(k=1;k<n;k++)
	{
		*(y+k) = 0;                    /*circular shift*/

		for(j=1;j<n;j++)
					*(x2+j)=*(a+(j-1));
					*(x2+0)=*(a+(n-1));
		for(i=0;i<n;i++)
		{
					*(a+i)=*(x2+i);
					*(y+k) = *(y+k) + (*(x+i)*(*(x2+i)));
		}
    }

	return y;

	free(y);
	free(a);
	free(x2);
}

float *convolution_LPF(float *x, float *h, int n, int m)
{
	float *y, *a, *x2;
	int i, j, k;

	if(n-m !=0)
	{
		if(n>m)
		{
			for(i=m; i<n; i++)
			{
				*(h+i) = 0;
				m = n;
			}
		}
		else
		{
			for(i=n; i<m; i++)
			{
				*(x+i) = 0;
				n = m;
			}
		}
	}

	y = (float *)calloc(sizeof(float), (n));
	a = (float *)calloc(sizeof(float), (n));
	x2 = (float *)calloc(sizeof(float), (n));


	*(y+0) = 0;
	*(a+0) = *(h+0);

	for(j=1;j<n;j++)            /*folding h(n) to h(-n)*/
		*(a+j) = *(h+(n-j));

    /*Circular convolution*/
    for(i=0;i<n;i++)
		*(y+0) = *(y+0) + (*(x+i) * (*(a+i)));

	for(k=1;k<n;k++)
	{
		*(y+k) = 0;                    /*circular shift*/

		for(j=1;j<n;j++)
					*(x2+j)=*(a+(j-1));
					*(x2+0)=*(a+(n-1));
		for(i=0;i<n;i++)
		{
					*(a+i)=*(x2+i);
					*(y+k) = *(y+k) + (*(x+i)*(*(x2+i)));
		}
    }

	return y;

	free(y);
	free(a);
	free(x2);

}

float * downsample(float *p, int len)
{
	int i, j;
	//float p1[1];
	float *ds;

	ds = (float *) malloc(sizeof(float)*(len/2));

	for(i=0,j=0; i<len/2; i++,j++)
		*(ds+i) = *(p+i+j);

	return ds;

	free(ds);
}

float mean_abs(float *p, int length)
{
	int i=0;
	float sum=0, mean;

	for(i=0; i<length; i++)
	{
		if(*(p+i) >= 0)
			sum = sum + (*(p+i));
		else
			sum = sum +(*(p+i)*(-1));
	}

	mean = (float) sum/length;

	return mean;
}

float linreg(float p[], int N_1)
{
	int i;
	float sum_x=0, sum_y=0, sum_xy=0, sum_x2=0, m, temp=0;

	for(i=0; i<=N_1; i++)
		sum_x = sum_x + log10(pow(2,i));
	//printf("%f\n", sum_x);

	for(i=0; i<=N_1; i++)
		sum_x2 = sum_x2 + (log10(pow(2,i))*log10(pow(2,i)));
	//printf("%f\n", sum_x2);

	for(i=0; i<=N_1; i++)
	{
		temp = p[i];
		if(temp>0 || temp<0)
			sum_y = sum_y + log10 (temp);
	}
	//printf("%f\n", sum_y);

	for(i=0; i<=N_1; i++)
	{
		temp = p[i];
		if(temp>0 ||temp<0)
			sum_xy = sum_xy + (log10(pow(2,i)) * log10(temp));
	}
	//printf("%f\n", sum_xy);

	m = ((N_1+1)*sum_xy - sum_x*sum_y) / ((N_1+1)*sum_x2 - pow(sum_x, 2));

	printf("Slope = %f\t H = 1-(slope)/2 = %f\n", m, 1-(m/2));

	return m;
}

Thank you...

Yours faithfully,

Priyanka G. Pawar

S. Y. M. Tech(Electronics-Digital Systems),

College of Engineering, Pune, Maharashtra.

0 Titusrathinaraj Stalin over 10 years ago in reply to Priyanka Pawar

TI__Guru** 116100 points

Hi Priyanka,

I'm getting the following results with your code.

N=4
32
1st Convolution output with HPF:
1st Downsampled output:
Mean=nan
1st Convolution output with LPF:
1st Downsampled output:
Mean=nan
Mean = 0.000000 Mean = nan Mean = 0.000000 Mean = 0.000000 Mean = 0.000000 Slope = 0.000000
Slope = H + 0.5, or H=1-Beta/2 H = 1.000000

Is this result are you expecting ?
And I'm not getting any problem just simply I ran the program.

0 Titusrathinaraj Stalin over 10 years ago in reply to Titusrathinaraj Stalin

TI__Guru** 116100 points

Sorry for the delayed responses on this due to other priority tasks :-)

"Can't find a source file at "c:\docume~1\win_xp\locals~1\temp\tia672~1\src/exit.c" Locate the file or edit the source lookup path to include its location."

This is not a problem, it means the program execution get completed.
You can ignore this message.

0 Titusrathinaraj Stalin over 10 years ago in reply to Priyanka Pawar

TI__Guru** 116100 points

Hi Priyanka,

I have checked by step by step debugging, when it is returning from function convolution_HPF It is not printing the output in main...

Now I'm getting the values like below after one modification , refer to the attached file.

I've seen "LENGTH" variable got "0" instead of "32" ,this value got cleared after "convolution_HPF" this function executed. So I've initialized the LENGTH to 32 again and got the following results.

Let us know if any issues.

Source code:

#include<stdio.h>
#include<math.h>
#include<stdlib.h>
//#include<malloc.h>

float* convolution_HPF(float *, float *, int, int); //Prototype
float* convolution_LPF(float *, float *, int, int); //Prototype
float* downsample(float *, int);                       //Prototype
float mean_abs(float *, int);                          //Prototype

#define L 16 //Length of input data
#define N floor(log (L)/log (2)) // levels

//coefficients
static float LPF_COEF[32] = {0.0031892209253436892,
    0.03490771432362905,
    0.1650642834886438,
    0.43031272284545874,
    0.6373563320829833,
    0.44029025688580486,
    -0.08975108940236352,
    -0.3270633105274758,
    -0.02791820813292813,
    0.21119069394696974,
    0.027340263752899923,
    -0.13238830556335474,
    -0.006239722752156254,
    0.07592423604445779,
    -0.007588974368642594,
    -0.036888397691556774,
    0.010297659641009963,
    0.013993768859843242,
    -0.006990014563390751,
    -0.0036442796214883506,
    0.00312802338120381,
    0.00040789698084934395,
    -0.0009410217493585433,
    0.00011424152003843815,
    0.00017478724522506327,
    -6.103596621404321e-05,
    -1.394566898819319e-05,
    1.133660866126152e-05,
    -1.0435713423102517e-06,
    -7.363656785441815e-07,
    2.3087840868545578e-07,
    -2.1093396300980412e-08};

static float HPF_COEF[32] = {-2.1093396300980412e-08,
    -2.3087840868545578e-07,
    -7.363656785441815e-07,
    1.0435713423102517e-06,
    1.133660866126152e-05,
    1.394566898819319e-05,
    -6.103596621404321e-05,
    -0.00017478724522506327,
    0.00011424152003843815,
    0.0009410217493585433,
    0.00040789698084934395,
    -0.00312802338120381,
    -0.0036442796214883506,
    0.006990014563390751,
    0.013993768859843242,
    -0.010297659641009963,
    -0.036888397691556774,
    0.007588974368642594,
    0.07592423604445779,
    0.006239722752156254,
    -0.13238830556335474,
    -0.027340263752899923,
    0.21119069394696974,
    0.02791820813292813,
    -0.3270633105274758,
    0.08975108940236352,
    0.44029025688580486,
    -0.6373563320829833,
    0.43031272284545874,
    -0.1650642834886438,
    0.03490771432362905,
    -0.0031892209253436892};

main()
{
   float data[L]={-0.1114,
   -0.2036,
    0.0458,
   -0.0011,
    0.0131,
    0.0536,
   -0.0398,
   -0.0798,
   -0.0663,
   -0.0776,
   -0.1351,
   -0.0293,
    0.0932,
   -0.0145,
   -0.0348,
    0.0047};
   float *ccout_HPF, *ccout_LPF, *dsout_HPF, *dsout_LPF, *temp1, *temp2, mean[5], slope;
   int i, LENGTH, N_1, k=0, r, l=1, prv_LENGTH;

   N_1 = (int) N;
   printf("N=%d\n", N_1);

   //1st-level
   r=pow(2,k);
   LENGTH = L/r;    //Length of output sequence
   if(L<32)
       LENGTH = 32;
   printf("%d\n", LENGTH);

   ccout_HPF = (float *) calloc(sizeof(float), LENGTH);        //ptr to Array storing values of convolution with HPF
   dsout_HPF = (float *) calloc(sizeof(float), (LENGTH/2));   //ptr to Array storing values of downsample output
   ccout_LPF = (float *) calloc(sizeof(float), LENGTH);        //ptr to Array storing values of convolution with LPF
   dsout_LPF = (float *) calloc(sizeof(float), (LENGTH/2));   //ptr to Array storing values of downsample output

   printf("Debug : LENGTH 1 %d\n",LENGTH);

   printf("%dst Convolution output with HPF: \n", k+1);
   ccout_HPF = convolution_HPF(data, HPF_COEF, L/r, 32);

   printf("Debug : LENGTH 2 %d\n",LENGTH);

   LENGTH = 32;

   printf("Debug : LENGTH 3 %d\n",LENGTH);

   for(i=0; i<LENGTH; i++)
   {
       printf("y[%d] = %f\n", i, *(ccout_HPF+i));
   }

   printf("Debug : LENGTH 4 %d\n",LENGTH);

   printf("%dst Downsampled output: \n", k+1);
   dsout_HPF = downsample(ccout_HPF, LENGTH);
   //for(i=0; i<LENGTH/2; i++)
       //printf("y[%d] = %f\n", i, *(dsout_HPF+i));

   mean[0] = mean_abs(dsout_HPF, LENGTH/2);
   printf("Mean=%f\n", mean[0]);

   printf("%dst Convolution output with LPF: \n", k+1);
   ccout_LPF = convolution_LPF(data, LPF_COEF, L/r, 32);
   //for(i=0; i<LENGTH; i++)
       //printf("y[%d] = %f\n", i, *(ccout_LPF+i));

   printf("%dst Downsampled output: \n", k+1);
   dsout_LPF = downsample(ccout_LPF, LENGTH);
   //for(i=0; i<LENGTH/2; i++)
       //printf("y[%d] = %f\n", i, *(dsout_LPF+i));

   temp1 = (float *) calloc(sizeof(float), LENGTH/2);
    for(i=0; i<(LENGTH/2); i++)
           *(temp1+i) = *(dsout_LPF+i);
   //for(i=0; i<LENGTH/2; i++)
       //printf("y[%d] = %f\n", i, *(temp1+i));
   prv_LENGTH = LENGTH/2;

   free(ccout_HPF);
   free(ccout_LPF);
   free(dsout_HPF);
   free(dsout_LPF);

   for(k=1, l=1; k<N_1&&l<N_1; k++, l++)                       //2nd to N_1th
   {
       //k=k+1;
       if((LENGTH/2)<=32)
           LENGTH = 32;
       else
       {
           //r=pow(2,k);
            LENGTH = LENGTH/2;
       }
       printf("%d\n", LENGTH);

       temp2 = (float *) calloc(sizeof(float), LENGTH);
       ccout_HPF = (float *) calloc(sizeof(float), LENGTH);
       dsout_HPF = (float *) calloc(sizeof(float), (LENGTH/2));
       ccout_LPF = (float *) calloc(sizeof(float), LENGTH);
       dsout_LPF = (float *) calloc(sizeof(float), (LENGTH/2));

       for(i=0; i<prv_LENGTH; i++)
           *(temp2+i) = *(temp1+i);
       for(i=25; i<LENGTH; i++)
           *(temp2+i) = 0;

       printf("%dth Convolution output with HPF: \n", k+1);
       ccout_HPF = convolution_HPF(temp2, HPF_COEF, LENGTH, 32);
       //for(i=0; i<LENGTH; i++)
           //printf("y[%d] = %f\n", i, *(ccout_HPF+i));

       printf("%dth Downsampled output: \n", k+1);
       dsout_HPF = downsample(ccout_HPF, LENGTH);
       //for(i=0; i<LENGTH/2; i++)
           //printf("y[%d] = %f\n", i, *(dsout_HPF+i));

       mean[l] = mean_abs(dsout_HPF, LENGTH/2);
       printf("Mean=%f\n", mean[l]);

       printf("%dth Convolution output with LPF: \n", k+1);
       ccout_LPF = convolution_LPF(temp2, LPF_COEF, LENGTH, 32);
       //for(i=0; i<LENGTH; i++)
           //printf("y[%d] = %f\n", i, *(ccout_LPF+i));

       printf("%dth Downsampled output: \n", k+1);
       dsout_LPF = downsample(ccout_LPF, LENGTH);
       //for(i=0; i<LENGTH/2; i++)
           //printf("y[%d] = %f\n", i, *(dsout_LPF+i));

       for(i=0; i<LENGTH/2; i++)
               *(temp1+i) = *(dsout_LPF+i);
       prv_LENGTH = LENGTH/2;

       //printf("\n");
       //for(i=0; i<LENGTH/2; i++)
           //printf("y[%d] = %f\n", i, *(temp1+i));

       free(ccout_HPF);
       free(ccout_LPF);
       free(dsout_HPF);
       free(dsout_LPF);
       free(temp2);

   }

   for(i=LENGTH/2; i<L; i++)
       *(temp1+i) = 0;
   mean[l] = mean_abs(temp1, LENGTH/2);
       printf("Mean=%f\n", mean[l]);

   for(i=0; i<=N; i++)
       printf("Mean = %f\t", mean[i]);

   slope = (log10(mean[4])-log10(mean[0]))/(log10(16.0)-log10(1.0));

   printf("Slope = %f\n", slope);
   printf("Slope = H + 0.5,\tor H=1-Beta/2 \t H = %f\n", 1-(slope/2));

   free(temp1);

}

float *convolution_HPF(float *x, float *h, int n, int m)
{
   float *y, *a, *x2;
   int i, j, k;

   if(n-m !=0)
   {
       if(n>m)
       {
           for(i=m; i<n; i++)
           {
               *(h+i) = 0;
               m = n;
           }
       }
       else
       {
           for(i=n; i<m; i++)
           {
               *(x+i) = 0;
               n = m;
           }
       }
   }

   y = (float *)calloc(sizeof(float), (n));
   a = (float *)calloc(sizeof(float), (n));
   x2 = (float *)calloc(sizeof(float), (n));

   *(y+0) = 0;
   *(a+0) = *(h+0);

   for(j=1;j<n;j++)
       *(a+j) = *(h+(n-j));

    for(i=0;i<n;i++)
       *(y+0) = *(y+0) + (*(x+i) * (*(a+i)));

   for(k=1;k<n;k++)
   {
       *(y+k) = 0;

       for(j=1;j<n;j++)
                   *(x2+j)=*(a+(j-1));
                   *(x2+0)=*(a+(n-1));
       for(i=0;i<n;i++)
       {
                   *(a+i)=*(x2+i);
                   *(y+k) = *(y+k) + (*(x+i)*(*(x2+i)));
       }
    }

   free(y);

   return y;

}

float *convolution_LPF(float *x, float *h, int n, int m)
{
   float *y, *a, *x2;
   int i, j, k;

   if(n-m !=0)
   {
       if(n>m)
       {
           for(i=m; i<n; i++)
           {
               *(h+i) = 0;
               m = n;
           }
       }
       else
       {
           for(i=n; i<m; i++)
           {
               *(x+i) = 0;
               n = m;
           }
       }
   }

   y = (float *)calloc(sizeof(float), (n));
   a = (float *)calloc(sizeof(float), (n));
   x2 = (float *)calloc(sizeof(float), (n));

   *(y+0) = 0;
   *(a+0) = *(h+0);

   for(j=1;j<n;j++)
       *(a+j) = *(h+(n-j));

    /*Circular convolution*/
    for(i=0;i<n;i++)
       *(y+0) = *(y+0) + (*(x+i) * (*(a+i)));

   for(k=1;k<n;k++)
   {
       *(y+k) = 0;

       for(j=1;j<n;j++)
                   *(x2+j)=*(a+(j-1));
                   *(x2+0)=*(a+(n-1));
       for(i=0;i<n;i++)
       {
                   *(a+i)=*(x2+i);
                   *(y+k) = *(y+k) + (*(x+i)*(*(x2+i)));
       }
    }

   free(y);

   return y;

}

float * downsample(float *p, int len)
{
   int i, j;
   //float p1[1];
   float *ds;

   ds = (float *) malloc(sizeof(float)*(len/2));

   for(i=0,j=0; i<len/2; i++,j++)
       *(ds+i) = *(p+i+j);

   free(ds);

   return ds;

}

float mean_abs(float *p, int length)
{
   int i=0;
   float sum=0, mean;

   for(i=0; i<length; i++)
   {
       if(*(p+i) >= 0)
           sum = sum + (*(p+i));
       else
           sum = sum +(*(p+i)*(-1));
   }

   mean = (float) sum/length;

   return mean;
}

Console Log:

N=4

Debug : LENGTH 1 32

1st Convolution output with HPF:

Debug : LENGTH 2 0

Debug : LENGTH 3 32

y[0] = -0.074030

y[1] = 0.019931

y[2] = 0.057276

y[3] = -0.020523

y[4] = -0.067938

y[5] = 0.061224

y[6] = 0.022540

y[7] = -0.063219

y[8] = 0.034835

y[9] = 0.001899

y[10] = -0.012462

y[11] = 0.007265

y[12] = -0.000891

y[13] = 0.000123

y[14] = -0.003094

y[15] = -0.001429

y[16] = 0.006547

y[17] = 0.006121

y[18] = -0.010845

y[19] = -0.015108

y[20] = 0.015214

y[21] = 0.027939

y[22] = -0.021206

y[23] = -0.041993

y[24] = 0.036271

y[25] = 0.048033

y[26] = -0.075282

y[27] = 0.001494

y[28] = 0.086954

y[29] = -0.122533

y[30] = 0.085519

y[31] = 0.011369

Debug : LENGTH 4 32

1st Downsampled output:

Mean=0.037772

1st Convolution output with LPF:

1st Downsampled output:

Mean=nan

Mean = 0.000000 Mean = nan Mean = 0.000000 Mean = 0.000000 Mean = 0.000000 Slope = 0.000000

Slope = H + 0.5, or H=1-Beta/2 H = 1.000000

0 Titusrathinaraj Stalin over 10 years ago in reply to Titusrathinaraj Stalin

TI__Guru** 116100 points

Hi Priyanka,
I'm closing this thread.
Any issues you can re-open this. :-)

0 Priyanka Pawar over 10 years ago in reply to Titusrathinaraj Stalin

Prodigy 90 points

Ok, Thank you for your support.

I will contact you again if there are another queries related to implementation with TMS320C6713.

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