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Artificial Neural Networks made easy with the FANN library

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28 Aug 2013CPOL24 min read 194.5K   10.6K   206  
Neural networks are typically associated with specialised applications, developed only by select groups of experts. This misconception has had a highly negative effect on its popularity. Hopefully, the FANN library will help fill this gap.
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>3.2. Running a Fixed Point ANN</A
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><P
>&#13;	Running a fixed point ANN is done much like running an ordinary ANN. The difference is that the inputs and outputs should be in fixed point
	representation. Furthermore the inputs should be restricted to be between -<VAR
CLASS="parameter"
>multiplier</VAR
> and <VAR
CLASS="parameter"
>multiplier</VAR
> to
	avoid integer overflow, where the <VAR
CLASS="parameter"
>multiplier</VAR
> is the value returned from
	<A
HREF="r1483.html"
><CODE
CLASS="function"
>fann_get_multiplier</CODE
></A
>. This multiplier is the value that a floating point number should
	be multiplied with, in order to be a fixed point number, likewise the output of the ANN should be divided by this multiplier in order to be between zero
	and one.
      </P
><P
>&#13;	To help using fixed point numbers, another function is provided.
	<A
HREF="r1467.html"
><CODE
CLASS="function"
>fann_get_decimal_point</CODE
></A
> which returns the decimal point. The decimal point is the
	position dividing the integer and fractional part of the fixed point number and is useful for doing operations on the fixed point inputs and outputs.
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><B
>Example 3-2. An example of a program written to support both fixed point and floating point numbers</B
></P
><PRE
CLASS="programlisting"
>&#13;
#include &#60;time.h&#62;
#include &#60;sys/time.h&#62;
#include &#60;stdio.h&#62;

#include "fann.h"

int main()
{
	fann_type *calc_out;
	unsigned int i;
	int ret = 0;

	struct fann *ann;
	struct fann_train_data *data;

	printf("Creating network.\n");

#ifdef FIXEDFANN
	ann = fann_create_from_file("xor_fixed.net");
#else
	ann = fann_create_from_file("xor_float.net");
#endif
	
	if(!ann){
		printf("Error creating ann --- ABORTING.\n");
		return 0;
	}

	printf("Testing network.\n");

#ifdef FIXEDFANN
	data = fann_read_train_from_file("xor_fixed.data");
#else
	data = fann_read_train_from_file("xor.data");
#endif

	for(i = 0; i &#60; data-&#62;num_data; i++){
		fann_reset_MSE(ann);
		calc_out = fann_test(ann, data-&#62;input[i], data-&#62;output[i]);
#ifdef FIXEDFANN
		printf("XOR test (%d, %d) -&#62; %d, should be %d, difference=%f\n",
		data-&#62;input[i][0], data-&#62;input[i][1], *calc_out, data-&#62;output[i][0], (float)fann_abs(*calc_out - data-&#62;output[i][0])/fann_get_multiplier(ann));

		if((float)fann_abs(*calc_out - data-&#62;output[i][0])/fann_get_multiplier(ann) &#62; 0.1){
			printf("Test failed\n");
			ret = -1;
		}
#else
		printf("XOR test (%f, %f) -&#62; %f, should be %f, difference=%f\n",
		data-&#62;input[i][0], data-&#62;input[i][1], *calc_out, data-&#62;output[i][0], (float)fann_abs(*calc_out - data-&#62;output[i][0]));
#endif
	}

	printf("Cleaning up.\n");
	fann_destroy_train(data);
	fann_destroy(ann);

	return ret;
}

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