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I am doing C programming for low pass filtering time series signal and then downsampling the signal. Is there any available C source code for dummies? For instance, given filter coefficients, h[n], and signal x[numberofSamples], how shall I get the filtered signal ?? Thanks______________________________
helen wrote:
> I am doing C programming for low pass filtering time series signal and then
> downsampling the signal.
>
> Is there any available C source code for dummies?
> For instance, given filter coefficients, h[n], and signal
> x[numberofSamples], how shall I get the filtered signal ??
>
> Thanks
>
Is this a finite impulse response filter (FIR), or an infinite impulse
response filter (IIR)?
If it's a FIR then you just take the last N samples and multiply them
sample-for-sample by the filter coefficients, so for sample n you'd use:
out[n] = sum from {k = max(0, n - N)} to n {x[n - k] * h[k]}
This article _may_ clear things up. Although it's written more for
control system design it does go into the implementation of IIR filters:
http://www.wescottdesign.com/articles/zTransform/z-transforms.html.
--
Tim Wescott
Wescott Design Services
http://www.wescottdesign.com
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______________________________helen wrote: > I am doing C programming for low pass filtering time series signal and then > downsampling the signal. > > Is there any available C source code for dummies? > For instance, given filter coefficients, h[n], and signal > x[numberofSamples], how shall I get the filtered signal ?? > You might find this useful: http://www.dspguru.com/info/faqs/firfaq.htm Good luck. -- Jim Thomas Principal Applications Engineer Bittware, Inc j...@bittware.com http://www.bittware.com (603) 226-0404 x536 There's a fine line between clever and stupid______________________________
I have the C++ code for convolution :
iCoefficients can be the FIR / IIR Coefficients, iIndex is the Index
number of the vector that is being filtered.
vec is the typedef for std::vector<double>
For an IIR filter your code would look like:
filteredData[i] Convolution(i,input,BCoefficients)-Convolution(i,filteredData,ACoefficients);
double Convolution(int iIndex, vec& iData, vec& iCoefficients)
/**< answer = conv(signal, filtercoefficients)*/
{
double answer = 0;
for(int l=0; l<iCoefficients.size();l++)
{
if((iIndex-l-1)>=0)
{
answer+= iData(iIndex-l-1)*iCoefficients(l);
}
else
{
answer+=0.0;
}
}
return answer;
}
As for calculating the coefficients of a low pass filter, try using the
billinear transform of if you need fast results, calculate the
coefficients in MATLAB and save them in your code.
______________________________