Store the settings required for performing EEMD.
Store the settings required for performing the EMD.
EmpiricalModeDecomposition.eemd — Method.eemd(input::Vector{Float64}, s::EEMDSetting)Return the IMFs computed by EEMD given the settings.
EmpiricalModeDecomposition.emd — Method.emd(input::Vector{Float64}, s::EMDSetting)Compute EMD of the input signal with given settings.
EmpiricalModeDecomposition.hht — Method.hht(signal::Vector{Float64}, s::EEMDSetting)Return the instantaneous energies and frequencies of the IMFS computed via the Hilbert-Huang transform with EEMD settings specified.
EmpiricalModeDecomposition.hht — Method.hht(signal::Vector{Float64}, s::EMDSetting)Return the instantaneous energies and frequencies of the IMFS computed via the Hilbert-Huang transform with EMD settings specified.
hilbert_transform(signal::Vector{Float64})Compute the Hilbert transform using the DFT approximation.
compute_instantaneous(signal::Vector{Float64}, imfs::Array{Float64, 2})Return the instantaneous energy and instantaneous frequencies of the IMFS in the signal.
evaluate_spline(x::Vector{Float64}, y::Vector{Float64}, n::Int64)Return spline generated by the first n elements of (x,y).
EmpiricalModeDecomposition.find_extrema! — Method.find_extrema!(x::Vector{Float64}, max_x::Vector{Float64}, max_y::Vector{Float64},
min_x::Vector{Float64}, min_y::Vector{Float64})Return the number of maxima, minima, and zero crossings of x after modifying maxx, maxy, minx, miny to contain the maxima and minima of x.
linear_extrapolate(x_0::Float64, y_0::Float64, x_1::Float64, y_1::Float64, x::Int64)Return the linear extrapolation of x based on x0, x1, y0, y1.
EmpiricalModeDecomposition.sift! — Method.sift!(input::Vector{Float64}, s::EMDSetting)Return the IMF that satisfies the given settings. In particular, it returns an IMF that satisifes the S number criterion that is found within the set number of siftings.