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Efficient FIR realtime filter

Project description

An efficient finite impulse response (FIR) filter class written in C++ with python wrapper.

The class offers also adaptive filtering using the least mean square (LMS) or normalised least mean square (NLMS) algorithm.


The preferred way to install is with pip:

pip3 install fir1

You can also install from source with python3 install:

git clone
cd fir1
python3 install


Realtime filtering

The filter is a realtime filter which always receives the values one by one so can process data as it comes in from an ADC converter. This is simulated here with the for loop:

import fir1
b = signal.firwin(999,0.1)
f = fir1.Fir1(b)
for i in range(len(noisy_signal)):
    clean_signal[i] = f.filter(noisy_signal[i])

The constructor Fir1(b) receives the coefficients and then filtering is performed with the method filter().

LMS adaptive filter

Please check the C++ code for examples and the main github page. The functions are identical.

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