From cd12f83f03b17af6d39a75b82db89d5be3d90227 Mon Sep 17 00:00:00 2001
From: Eric Kooistra <kooistra@astron.nl>
Date: Thu, 12 Dec 2024 16:57:38 +0100
Subject: [PATCH] Rename.
---
.../model/pfb_bunton_annotated/Gen_filter12.m | 2 +-
.../lofar2/model/readme_rtdsp_fir.txt | 32 +++++++++++++++++++
2 files changed, 33 insertions(+), 1 deletion(-)
create mode 100644 applications/lofar2/model/readme_rtdsp_fir.txt
diff --git a/applications/lofar2/model/pfb_bunton_annotated/Gen_filter12.m b/applications/lofar2/model/pfb_bunton_annotated/Gen_filter12.m
index 50b22e3bd5..2175d731c6 100644
--- a/applications/lofar2/model/pfb_bunton_annotated/Gen_filter12.m
+++ b/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')
diff --git a/applications/lofar2/model/readme_rtdsp_fir.txt b/applications/lofar2/model/readme_rtdsp_fir.txt
new file mode 100644
index 0000000000..e2178313ef
--- /dev/null
+++ b/applications/lofar2/model/readme_rtdsp_fir.txt
@@ -0,0 +1,32 @@
+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
--
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