dcrg.era

Functions

dcrg.era.Copy_of_solveERA

dcrg.era.Copy_of_solveERA(H1, P, D, Q, dt, df, ys, fmax)

Run solution for a different number of truncated model values Created by : R Cheung Contact: r.c.m.cheung@bristol.ac.uk Date: Oct 2019 Stabilisation Criteria

dcrg.era.chirp_dst

dcrg.era.chirp_dst(y, fs, fmin, fmax, varargin)

PSD [f,Pl,df] = psd(y,Fs,varargin) generate the power spectial density of the input y, with a sampling frequency of ‘Fs’ Created by : R Cheung Contact: r.c.m.cheung@bristol.ac.uk Date: Oct 2019

dcrg.era.genCorrelHankelMat

dcrg.era.genCorrelHankelMat(yi, alpha, tau, xi, zeta)

Generate Data-correlated Hankel Matrices Created by : R Cheung Contact: r.c.m.cheung@bristol.ac.uk Date: Oct 2019

tau = number of sample lag size(HH0) = [zeta+1,eta+1] Orient input matrix

dcrg.era.genCorrelSignal

dcrg.era.genCorrelSignal(yi, dt, nCorrel)

Generate correlated signal Created by : R Cheung Contact: r.c.m.cheung@bristol.ac.uk Date: Oct 2019

dcrg.era.genHankelMat

dcrg.era.genHankelMat(yi, alpha)

Generate Hankel Matrix Created by : R Cheung Contact: r.c.m.cheung@bristol.ac.uk Date: Oct 2019 Orient input matrix

dcrg.era.plotSVD

dcrg.era.plotSVD(D, varargin)

Plot singular values Created by : R Cheung Contact: r.c.m.cheung@bristol.ac.uk Date: Oct 2019

dcrg.era.runERA

dcrg.era.runERA(yi, samplingRate, fmax, alpha)

ERA Created by : R Cheung Contact: r.c.m.cheung@bristol.ac.uk Date: Oct 2019

Input : each column of yi is an input data channel prep

dcrg.era.runERACorrel

dcrg.era.runERACorrel(yi, samplingRate, fmax, alpha, nCorrel)

ERA using correlated input Created by : R Cheung Contact: r.c.m.cheung@bristol.ac.uk Date: Oct 2019

Input : each column of yi is an input data channel prep

dcrg.era.runERADC

dcrg.era.runERADC(yi, samplingRate, fmax, alpha, tau, xi, zeta)

ERA-DC Created by : R Cheung Contact: r.c.m.cheung@bristol.ac.uk Date: Oct 2019

Input : each column of yi is an input data channel prep

dcrg.era.solveCrudeERA

dcrg.era.solveCrudeERA(H1, P, D, Q, dt, df, ys, fmax, dTol, windowSize, makePlots)

Run solution for a different number of truncated model values Created by : R Cheung Contact: r.c.m.cheung@bristol.ac.uk Date: Oct 2019

dcrg.era.solveERA

dcrg.era.solveERA(H1, P, D, Q, dt, df, ys, fmax, outputs)

Run solution for a different number of truncated model values Created by : R Cheung Contact: r.c.m.cheung@bristol.ac.uk Date: Oct 2019 Stabilisation Criteria