FIR Filter with size(kernel) > size(buffer)

[HammieTime]

Hello. So I've been starting again with audio coding and decided to start with FIR filters.
I have a nice code that produces the windowed filter kernels properly.

However I have problem in a situation where the filter kernel (lets say nK) is larger than the audio buffer (lets say nFrames). I've tried to simulate the behaviour with matlab as it's easier to debug:

This is the main loop. x1 is the input signal with three sine frequencies.

for i=1:nFrames:length(x1)
startIndx=i;
in=x1(i:(i-1)+nFrames);
in_test=in-x1(i:i-1+nFrames);

[out,xPrev]=process_myFIR_v2(in,xPrev,nFrames,h, length(h));
y1(i:(i-1)+nFrames)=out;

end

Then I take the FFT's and compare the results with MATLAB's own filter(B,A,y) command.
The loop works just fine in cases where nK<=nFrames, as I said earlier. The problem obviously lies somewhere in process_myFIR_v2() function.
When FIR loop is calculating the previous values:
if (i < j)
tmp = tmp+kernel(j)*xPrev(j-i); - I am using 'inverted' previous x-vector 'xPrev' so that xPrev(index=0) gives the "most recent" value and xPrev(k-1) gives the latest required value for the kernel.

So this works in cases nK<nFrames - so the problem is in my pushback loop, where I'm pushing the most recent 'xPrev' values as follows:

xPrev(nF+1:nK-nF-1) = xPrev(1:nK-nF).

So the code looks like this:
%% Write the xPrev vector
if (kernelSize-1<=nFrames)
for k=1:1:kernelSize-1
xP(k)=x(nFrames-k+1);
end
else
% Pushback the previous xPrev to the end before inputting x to 1:nf
% Try using temporary storage 'xP2'
prevSize=kernelSize-1;
xP2=zeros(1,prevSize-nFrames);
for k=1:prevSize-nFrames
xP2(k)=xP(k);
end

% Write the input buffer to xPrev, inverted.
for n=1:1:nFrames
xP(n)=x(nFrames-n+1); % Copies input to first part of xPrev, reversed
end

% Insert temporary buffer xP2
for k=1:prevSize-nFrames
xP(nFrames+k)=xP2(k);
end

end

Unfortunately MATLAB uses the horrible indexing system starting from '1' so everything gets confusing when working with c++ in conjunction.
If anyone is willing to help, I'd much appreciate that.

EDIT:

Here's the filter frequency response when nK=296 (order of filter) and I'm using nFrames=200.
Figure(5) shows the filtered signal with my code and figure(6) is the MATLAB filter() function filtered signal (no previous values required etc). Samplerate is 24kHz

[Miles1981]

You need a temporary buffer the same length as nFrames. Start by making it like that, copy in a circular buffer the new buffer and make the FIR output.
Then once you have something that works, you can "optimize". Create nFrames/nk rounded up buffers. Each time you get a new buffer, rotate the past buffers and copy the new one in your list. Apply the FIR.
Just basic algorithm. Return to the basics first.
The end.

[HammieTime]

You need a temporary buffer the same length as nFrames. Start by making it like that, copy in a circular buffer the new buffer and make the FIR output.
Then once you have something that works, you can "optimize". Create nFrames/nk rounded up buffers. Each time you get a new buffer, rotate the past buffers and copy the new one in your list. Apply the FIR.
Just basic algorithm. Return to the basics first.
The end.

Thank you. I got it working now!

[Edouard Digital]

Hi Miles, talking about optimize buffers, we're looking for an expert on the subject, in the form of a consulting mission. Would you be interested?

You need a temporary buffer the same length as nFrames. Start by making it like that, copy in a circular buffer the new buffer and make the FIR output.
Then once you have something that works, you can "optimize". Create nFrames/nk rounded up buffers. Each time you get a new buffer, rotate the past buffers and copy the new one in your list. Apply the FIR.
Just basic algorithm. Return to the basics first.
The end.