Curtis Mattull
software implementing neural network trained with sine, tri, square wave inputs.
Revision 0:34aeffc5e6f0, committed 2016-10-04
- Comitter:
- cpm219
- Date:
- Tue Oct 04 23:31:44 2016 +0000
- Commit message:
- update to implement C++ instead of C.
Changed in this revision
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/main.cpp Tue Oct 04 23:31:44 2016 +0000
@@ -0,0 +1,126 @@
+//
+// File: ert_main.cpp
+//
+// Code generated for Simulink model 'neural_network3'.
+//
+// Model version : 1.7
+// Simulink Coder version : 8.10 (R2016a) 10-Feb-2016
+// C/C++ source code generated on : Tue Oct 04 18:06:54 2016
+//
+// Target selection: ert.tlc
+// Embedded hardware selection: ARM Compatible->ARM Cortex
+// Code generation objectives: Unspecified
+// Validation result: Not run
+//
+#include <stddef.h>
+#include <stdio.h> // This ert_main.c example uses printf/fflush
+#include "neural_network3.h" // Model's header file
+#include "rtwtypes.h"
+#include "mbed.h"
+
+//
+// Associating rt_OneStep with a real-time clock or interrupt service routine
+// is what makes the generated code "real-time". The function rt_OneStep is
+// always associated with the base rate of the model. Subrates are managed
+// by the base rate from inside the generated code. Enabling/disabling
+// interrupts and floating point context switches are target specific. This
+// example code indicates where these should take place relative to executing
+// the generated code step function. Overrun behavior should be tailored to
+// your application needs. This example simply sets an error status in the
+// real-time model and returns from rt_OneStep.
+//
+void rt_OneStep(void);
+void rt_OneStep(void)
+{
+ static boolean_T OverrunFlag = false;
+
+ // '<Root>/In1'
+ static real_T arg_In1[200] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };
+
+ // '<Root>/Out1'
+ static real_T arg_Out1[2];
+
+ // Disable interrupts here
+
+ // Check for overrun
+ if (OverrunFlag) {
+ rtmSetErrorStatus(neural_network3_M, "Overrun");
+ return;
+ }
+
+ OverrunFlag = true;
+
+ // Save FPU context here (if necessary)
+ // Re-enable timer or interrupt here
+ // Set model inputs here
+
+ // Step the model
+ neural_network3_custom(arg_In1, arg_Out1);
+
+ // Get model outputs here
+ printf("output: %f", arg_Out1);
+ // Indicate task complete
+ OverrunFlag = false;
+
+ // Disable interrupts here
+ // Restore FPU context here (if necessary)
+ // Enable interrupts here
+}
+
+//
+// The example "main" function illustrates what is required by your
+// application code to initialize, execute, and terminate the generated code.
+// Attaching rt_OneStep to a real-time clock is target specific. This example
+// illustrates how you do this relative to initializing the model.
+//
+int_T main(int_T argc, const char *argv[])
+{
+ // Unused arguments
+ (void)(argc);
+ (void)(argv);
+
+ // Initialize model
+ neural_network3_initialize();
+
+ // Attach rt_OneStep to a timer or interrupt service routine with
+ // period 0.2 seconds (the model's base sample time) here. The
+ // call syntax for rt_OneStep is
+ //
+ for(;;)
+ {
+ rt_OneStep();
+ wait(0.2);
+ }
+// printf("Warning: The simulation will run forever. "
+// "Generated ERT main won't simulate model step behavior. "
+// "To change this behavior select the 'MAT-file logging' option.\n");
+ fflush((NULL));
+ while (rtmGetErrorStatus(neural_network3_M) == (NULL)) {
+ // Perform other application tasks here
+ }
+
+ // Disable rt_OneStep() here
+
+ // Terminate model
+ neural_network3_terminate();
+ return 0;
+}
+
+//
+// File trailer for generated code.
+//
+// [EOF]
+//
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/mbed.bld Tue Oct 04 23:31:44 2016 +0000 @@ -0,0 +1,1 @@ +http://mbed.org/users/mbed_official/code/mbed/builds/25aea2a3f4e3 \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/neural_net_cpp_v1.lib Tue Oct 04 23:31:44 2016 +0000 @@ -0,0 +1,1 @@ +https://developer.mbed.org/users/cpm219/code/neural_net_cpp_test_v1/#7363365590dd