Rename.

applications/lofar2/model/pfb_bunton_annotated/Gen_filter12.m

@@ -103,4 +103,4 @@ title ('Response of fircls1 filter c and interpolated cl')
 grid
 
 clT = cl';
-save('cl.txt', 'clT', '-ascii', '-double')
+save('cl.dat', 'clT', '-ascii', '-double')

applications/lofar2/model/readme_rtdsp_fir.txt

+Author: Eric Kooistra, nov 2023
+
+* Practise DSP [1].
+
+* Try to reproduce LOFAR subband filter FIR coefficients using scipy instead
+  of MATLAB.
+  The pfs_coeff_final.m from the Filter Task Force (FTF) in 2005 use fircls1
+  with r_pass and r_stop to define the ripple. In addition it post applies a
+  Kaiser window with beta = 1 to make the filter attenuation a bit more deep
+  near the transition. The pfir_coeff.m from Apertif also uses fircls1.
+  Both use fircls1 with N = 1024 FIR coefficients and then Fourier
+  interpolation to achieve Ncoefs = 1024 * 16 FIR coefficients. Both scripts
+  can not exactly reproduce the actual LOFAR1 coefficients, therefore these
+  are loaded from a file Coeffs16384Kaiser-quant.dat
+
+* Try low pass filter design methods using windowed sync, firls, remez [2]
+  The windowed sync method, firls leased squares method and remez method all
+  yield comparable results, but firls and remez perform slightly better near
+  the transition band. The firls and remez functions from scipy.signal use
+  transition bandwidth and weights between pass and stop band to influence
+  the transition region and ripple. For remez the ripple is constant in the
+  pass band and stop band, for firls the ripple is largest near the band
+  transition.
+
+* It is possible to design a good FIR filter using Python scipy. Possibly with
+  some extra help of a filter design and analysis (FDA) tool like pyfda [3].
+
+[1] https://git.astron.nl/rtsd/rtdsp/-/blob/main/doc/dsp_study_erko.txt,
+    summary of DSP books
+[2] python package rtdsp and Jupyter notebooks, for radio telescope DSP
+    investigations in Python at https://git.astron.nl/rtsd/rtdsp
+[3] pyfda, dsp, at https://github.com/chipmuenk