/* Define Constants */
const int  knNUM_SAMPLES = 100000;           // Number of input samples, change as necessary

const float kfSamplingFrequency = 48000;
const float kfAveragingTime = 1000;          // Change as necessary
float fAveragedSamples = ( kfSamplingFrequency * kfAveragingTime)/1000;

const float fAvgThreshold = 0;           // To be determined 
float fAveragingConstant;                       

/* Input and Output Arrays */
float afInputSamples[knNUM_SAMPLES];
float afAveragedSamples[knNUM_SAMPLES];

/* Instantiate a cAveragingFilter object */
cAveragingFilter AvgFilterObj;

int main()
{
   AvgFilterObj.Load( knNUM_SAMPLES );

   AvgFilterObj.Process();

   return 0;
}

/* Constructor */
cAveragingFilter::cAveragingFilter() 
{
	fAveragingConstant = (float) exp( -2.15 / ( kfAveragingTime * kfSamplingFrequency ) );   
}

/* Destructor */
cAveragingFilter::~cAveragingFilter() { }

void cAveragingFilter::Load(int knNUM_SAMPLES)
{
	// This will be replaced by the routine that reads in the inputs
	// to the averaging filter.

	for ( int i = 0; i < knNUM_SAMPLES; i++ )
	{
		afInputSamples[i] = 1;
	}
}

void cAveragingFilter::Process()
{
   afAveragedSamples[0]  = afInputSamples[0];
   
   for ( int i = 1; i < knNUM_SAMPLES - 1; i++ )
   {
      afInputSamples[i] = abs(afInputSamples[i]);

	  // Check to see if the input value is higher than the threshold
	  if (afInputSamples[i] < fAvgThreshold)
	  {
	     afAveragedSamples[i] = afAveragedSamples[i-1];
	  }
	  else
	  {
	     afAveragedSamples[i] = ( 1 - fAveragingConstant ) * afInputSamples[i] + fAveragingConstant * afAveragedSamples[i-1];
	  }
   }
}

  /* intitialize y */

  y = 0;
  oldy = 0;

  for (;;) {

    x = GetNewX();
    y = (1 - a) * x + oldy;
    /* use new value of y for whatever you need */
    oldy = y;

  }