MATLAB Examples

Floating-Point Multiplication to Handle a Net Slope Correction

This example shows how to use floating-point multiplication to handle a net slope correction. When converting floating-point data types to fixed-point data types in the generated code, a net slope correction is one method of scaling fixed-point data types. Scaling the fixed-point data types avoids overflow conditions and minimizes quantization errors.

For processors that support efficient multiplication, using floating-point multiplication to handle a net slope correction improves code efficiency. If the net slope correction has a value that is not a power of two, using division improves precision.

Note: This example requires a Fixed-Point Designer™ license.

Contents

Example

In the model rtwdemo_float_mul_for_net_slope_correction, a Convert block converts an input signal from a floating-point data type to a fixed-point data type. The net slope correction has a value of 3.

model = 'rtwdemo_float_mul_for_net_slope_correction';
open_system(model);

Generate Code

Create a temporary folder for the build and inspection process.

currentDir = pwd;
[~,cgDir] = rtwdemodir();

Build the model.

rtwbuild(model)
### Starting build procedure for model: rtwdemo_float_mul_for_net_slope_correction
### Successful completion of build procedure for model: rtwdemo_float_mul_for_net_slope_correction

In these lines of rtwdemo_float_mul_for_net_slope_correction.c code, the code generator divides the input signal by 3.0F .

cfile = fullfile(cgDir,'rtwdemo_float_mul_for_net_slope_correction_ert_rtw',...
    'rtwdemo_float_mul_for_net_slope_correction.c');
rtwdemodbtype(cfile,'/* Model step', '/* Model initialize', 1, 0);
/* Model step function */
void rtwdemo_float_mul_for_net_slope_correction_step(void)
{
  /* Outport: '<Root>/Output' incorporates:
   *  DataTypeConversion: '<Root>/Data Type Conversion'
   *  Inport: '<Root>/Input'
   */
  rtY.Output = (int16_T)(real32_T)floor((real_T)(rtU.Input / 3.0F));
}

Enable Optimization

  1. Open the Configuration Parameters dialog box.
  2. On the Optimization pane, select Use floating-point multiplication to handle net slope corrections. This optimization is on by default.

Alternatively, you can use the command-line API to enable the optimization.

set_param(model, 'UseFloatMulNetSlope', 'on');

Generate Code with Optimization

rtwbuild(model)
### Starting build procedure for model: rtwdemo_float_mul_for_net_slope_correction
### Successful completion of build procedure for model: rtwdemo_float_mul_for_net_slope_correction

In the optimized code, the code generator multiplies the input signal by the reciprocal of 3.0F , that is 0.333333343F .

rtwdemodbtype(cfile,'/* Model step', '/* Model initialize', 1, 0);
/* Model step function */
void rtwdemo_float_mul_for_net_slope_correction_step(void)
{
  /* Outport: '<Root>/Output' incorporates:
   *  DataTypeConversion: '<Root>/Data Type Conversion'
   *  Inport: '<Root>/Input'
   */
  rtY.Output = (int16_T)(real32_T)floor((real_T)(rtU.Input * 0.333333343F));
}

Close the model and the code generation report.

bdclose(model)
rtwdemoclean;
cd(currentDir)