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Discrete-time, overlap-add, FIR filter


Hd = dfilt.fftfir(b,len)
Hd = dfilt.fftfir(b)
Hd = dfilt.fftfir


This object uses the overlap-add method of block FIR filtering, which is very efficient for streaming data.

Hd = dfilt.fftfir(b,len) returns a discrete-time, FFT, FIR filter, Hd, with numerator coefficients, b and block length, len. The block length is the number of input points to use for each overlap-add computation.

Hd = dfilt.fftfir(b) returns a discrete-time, FFT, FIR filter, Hd, with numerator coefficients, b and block length, len=100.

Hd = dfilt.fftfir returns a default, discrete-time, FFT, FIR filter, Hd, with the numerator b=1 and block length, len=100. This filter passes the input through to the output unchanged.

    Note   When you use a dfilt.fftfir object to filter, the input signal length must be an integer multiple of the object's block length, len. The resulting number of FFT points = (filter length + the block length - 1). The filter is most efficient if the number of FFT points is a power of 2.

The fftfir uses an overlap-add block processing algorithm, which is represented as follows,

where len is the block length and M is the length of the numerator-1, (length(b)-1), which is also the number of states. The output of each convolution is a block that is longer than the input block by a tail of (length(b)-1) samples. These tails overlap the next block and are added to it. The states reported by dfilt.fftfir are the tails of the final convolution.


Create an FFT FIR discrete-time filter with coefficients from a 30th order lowpass equiripple design:

b = firpm(30,[0 .1 .2 .5]*2,[1 1 0 0]);
Hd = dfilt.fftfir(b);
% To obtain frequency domain coefficients
% used in filtering
Coeffs = fftcoeffs(Hd);

Introduced in R2011a

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