private List <double> fIRFilter(List <double> Xn, int filter_type, double fc1, double fc2, double t_width, double stop_attenuation, double fs)
{
List <double> res = new List <double>();
List <double> Hd = new List <double>();
List <double> Wn = new List <double>();
List <double> Hn = new List <double>();
int N = 0, fullSize = 0;
Wn = calculatWindowFunction(stop_attenuation, t_width, ref N, ref fullSize);
Hd = calculateFilterFunction(filter_type, fc1, fc2, fs, t_width, N);
for (int i = 0; i <= N; i++)
{
Hn.Add(Hd[i] * Wn[i]);
}
//int j = N - 1;
//for (int i = N + 1; i < fullSize; i++)
//{
// Hn.Add(Hn[j]);
// j--;
//}
ConvolutionAndCorrelation obj = new ConvolutionAndCorrelation();
string p = "D:\\My Collage's Stages\\Fourth Year\\Second Semester\\Signal Processing\\Labs\\The Package\\Results\\FIR\\CoffOfFIR.txt";
obj.SaveInFile(p, Hn);
ConvolutionAndCorrelation c = new ConvolutionAndCorrelation();
res = c.Convolution(Xn, Hn);
p = "D:\\My Collage's Stages\\Fourth Year\\Second Semester\\Signal Processing\\Labs\\The Package\\Results\\FIR\\AfterConvolution.txt";
obj.SaveInFile(p, Hn);
return(res);
}
private void btnDone_Click(object sender, EventArgs e)
{
filterType = comboBox1.SelectedIndex;
cutOffFreq1 = double.Parse(txtboxFC1.Text);
if (filterType == 2 || filterType == 3)
{
cutOffFreq2 = double.Parse(txtBoxFC2.Text);
}
transitionWidth = double.Parse(txtBoxTransitionWidth.Text);
stopbandAtten = double.Parse(txtBoxStopbandAttenuation.Text);
samplingFreq = double.Parse(txtBoxSamplingFrequency.Text);
transitionWidth = transitionWidth / samplingFreq; //DeltaF
if (rbuttonDownSampling.Checked)
{
m = int.Parse(txtBoxDownSampling.Text);
result = fIRFilter(signal, filterType, cutOffFreq1, cutOffFreq2, transitionWidth, stopbandAtten, samplingFreq);
downSamplingResult = downSampling(result, m);
finalResult = downSamplingResult;
}
else if (rbuttonUpSampling.Checked)
{
l = int.Parse(txtBoxUpSampling.Text);
upSamplingResult = upSampling(signal, l);
result = fIRFilter(upSamplingResult, filterType, cutOffFreq1, cutOffFreq2, transitionWidth, stopbandAtten, samplingFreq);
finalResult = result;
}
else if (rbuttonUpDownSampling.Checked)
{
m = int.Parse(txt2DownSampling.Text);
l = int.Parse(txt1UpSampling.Text);
upSamplingResult = upSampling(signal, l);
result = fIRFilter(upSamplingResult, filterType, cutOffFreq1, cutOffFreq2, transitionWidth, stopbandAtten, samplingFreq);
downSamplingResult = downSampling(result, m);
finalResult = downSamplingResult;
}
else
{
result = fIRFilter(signal, filterType, cutOffFreq1, cutOffFreq2, transitionWidth, stopbandAtten, samplingFreq);
finalResult = result;
}
ConvolutionAndCorrelation obj = new ConvolutionAndCorrelation();
string p = "D:\\My Collage's Stages\\Fourth Year\\Second Semester\\Signal Processing\\Labs\\The Package\\Results\\FIR\\resultOfFIR.txt";
obj.SaveInFile(p, finalResult);
MessageBox.Show("the filter have done and the file is saved successfully :D", "Done", MessageBoxButtons.OK);
}
private List <double> upSampling(List <double> list, int factor)
{
List <double> sampled = new List <double>();
for (int i = 0; i < list.Count; i++)
{
sampled.Add(list[i]);
for (int j = 0; j < (factor - 1); j++)
{
sampled.Add(0);
}
}
ConvolutionAndCorrelation obj = new ConvolutionAndCorrelation();
string p = "D:\\My Collage's Stages\\Fourth Year\\Second Semester\\Signal Processing\\Labs\\The Package\\Results\\FIR\\UpsampledData.txt";
obj.SaveInFile(p, sampled);
return(sampled);
}
private void btnCovolution_Click(object sender, EventArgs e)
{
ConvolutionAndCorrelation c = new ConvolutionAndCorrelation();
c.Show();
}
