JuliaDynamics/ComplexityMeasures.jl
Improve `PowerSpectrum` estimator: add threhsold
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#104 geöffnet am 27.09.2022
good first issueimprovement
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Beschreibung
The power spectrum estimator will yield rather uncoverged results for small timeseries of regular signals, due to the noise induced by the FOurier transform affecting the signal a lot. We should add a threshold that reduces to 0 all spectral power less than this threshold. This would make the results much more reasonable for signals, and better for normalized. Here is the example code I have:
using DynamicalSystems
N1, N2, a = 101, 100001, 10
for N in (N1, N2)
t = LinRange(0, 2*a*π, N)
x = sin.(t) # periodic
y = sin.(t .+ cos.(t/0.5)) # periodic, complex spectrum
z = sin.(rand(1:15, N) ./ rand(1:10, N)) # random
w = trajectory(Systems.lorenz(), N÷10; Δt = 0.1, Ttr = 100)[:, 1] # chaotic
for q in (x, y, z, w)
h = entropy(q, PowerSpectrum())
n = entropy_normalized(q, PowerSpectrum())
println("entropy: $(h), normalized: $(n).")
end
end