mirror of https://github.com/mpastell/Weave.jl
151 lines
3.4 KiB
Plaintext
151 lines
3.4 KiB
Plaintext
---
|
|
author: "Matti Pastell"
|
|
title: "FIR filter design with Julia"
|
|
date: "21th April 2016"
|
|
---
|
|
|
|
|
|
|
|
# Introduction
|
|
|
|
|
|
This an example of a julia script that can be published using
|
|
[Weave](http://weavejl.mpastell.com/dev/usage/).
|
|
The script can be executed normally using Julia
|
|
or published to HTML or pdf with Weave.
|
|
Text is written in markdown in lines starting with "`#'` " and code
|
|
is executed and results are included in the published document.
|
|
|
|
|
|
Notice that you don't need to define chunk options, but you can using
|
|
`#+`. just before code e.g. `#+ term=True, caption='Fancy plots.'`.
|
|
If you're viewing the published version have a look at the
|
|
[source](FIR_design_plots.jl) to see the markup.
|
|
|
|
|
|
<!-- this setup dependencies, but doesn't appear in the generated document -->
|
|
|
|
|
|
|
|
|
|
# FIR Filter Design
|
|
|
|
|
|
We'll implement lowpass, highpass and ' bandpass FIR filters. If
|
|
you want to read more about DSP I highly recommend [The Scientist
|
|
and Engineer's Guide to Digital Signal
|
|
Processing](http://www.dspguide.com/) which is freely available
|
|
online.
|
|
|
|
|
|
## Calculating frequency response
|
|
|
|
|
|
DSP.jl package doesn't (yet) have a method to calculate the
|
|
the frequency response of a FIR filter so we define it:
|
|
|
|
~~~~{.julia}
|
|
using Plots, DSP
|
|
gr()
|
|
|
|
function FIRfreqz(b::Array, w = range(0, stop=π, length=1024))
|
|
n = length(w)
|
|
h = Array{ComplexF32}(undef, n)
|
|
sw = 0
|
|
for i = 1:n
|
|
for j = 1:length(b)
|
|
sw += b[j]*exp(-im*w[i])^-j
|
|
end
|
|
h[i] = sw
|
|
sw = 0
|
|
end
|
|
return h
|
|
end
|
|
~~~~~~~~~~~~~
|
|
|
|
~~~~
|
|
FIRfreqz (generic function with 2 methods)
|
|
~~~~
|
|
|
|
|
|
|
|
|
|
|
|
## Design Lowpass FIR filter
|
|
|
|
|
|
Designing a lowpass FIR filter is very simple to do with DSP.jl, all you
|
|
need to do is to define the window length, cut off frequency and the
|
|
window. We will define a lowpass filter with cut off frequency at 5Hz for a signal
|
|
sampled at 20 Hz.
|
|
We will use the Hamming window, which is defined as:
|
|
$w(n) = \alpha - \beta\cos\frac{2\pi n}{N-1}$, where $\alpha=0.54$ and $\beta=0.46$
|
|
|
|
~~~~{.julia}
|
|
fs = 20
|
|
f = digitalfilter(Lowpass(5, fs = fs), FIRWindow(hamming(61)))
|
|
w = range(0, stop=pi, length=1024)
|
|
h = FIRfreqz(f, w)
|
|
~~~~~~~~~~~~~
|
|
|
|
~~~~
|
|
1024-element Array{Complex{Float32},1}:
|
|
1.0f0 + 0.0f0im
|
|
0.99546844f0 + 0.095055714f0im
|
|
0.98191506f0 + 0.1892486f0im
|
|
0.95946306f0 + 0.28172377f0im
|
|
0.9283168f0 + 0.37164196f0im
|
|
0.8887594f0 + 0.45818728f0im
|
|
0.84115064f0 + 0.54057467f0im
|
|
0.7859234f0 + 0.618057f0im
|
|
0.72357976f0 + 0.6899319f0im
|
|
0.65468615f0 + 0.7555481f0im
|
|
⋮
|
|
0.00043952762f0 - 0.00041908873f0im
|
|
0.0005152718f0 - 0.00040521423f0im
|
|
0.0005873293f0 - 0.00037745363f0im
|
|
0.0006531789f0 - 0.0003367371f0im
|
|
0.0007105166f0 - 0.00028444792f0im
|
|
0.0007573364f0 - 0.00022237403f0im
|
|
0.0007920005f0 - 0.00015264557f0im
|
|
0.0008132961f0 - 7.766036f-5im
|
|
0.0008204784f0 - 3.1148685f-18im
|
|
~~~~
|
|
|
|
|
|
|
|
|
|
|
|
## Plot the frequency and impulse response
|
|
|
|
|
|
The next code chunk is executed in term mode, see the [script](FIR_design.jl) for syntax.
|
|
|
|
~~~~{.julia}
|
|
julia> h_db = log10.(abs.(h));
|
|
|
|
julia> ws = w/pi*(fs/2)
|
|
0.0:0.009775171065493646:10.0
|
|
~~~~~~~~~~~~~
|
|
|
|
~~~~{.julia}
|
|
plot(ws, h_db,
|
|
xlabel = "Frequency (Hz)", ylabel = "Magnitude (db)")
|
|
~~~~~~~~~~~~~
|
|
|
|
![](figures/FIR_design_5_1.png)\
|
|
|
|
|
|
|
|
|
|
And again with default options
|
|
|
|
~~~~{.julia}
|
|
h_phase = unwrap(-atan.(imag.(h),real.(h)))
|
|
plot(ws, h_phase,
|
|
xlabel = "Frequency (Hz)", ylabel = "Phase (radians)")
|
|
~~~~~~~~~~~~~
|
|
|
|
![](figures/FIR_design_6_1.png)\
|
|
|