Mercurial > hg > ltpda
diff m-toolbox/classes/+utils/@math/psdzfit.m @ 0:f0afece42f48
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author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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date | Wed, 23 Nov 2011 19:22:13 +0100 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/m-toolbox/classes/+utils/@math/psdzfit.m Wed Nov 23 19:22:13 2011 +0100 @@ -0,0 +1,655 @@ +% PSDZFIT: Fit discrete partial fraction model to PSD +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% DESCRIPTION: +% +% Fits discrete partial fractions model to power spectral density. The +% function is able to fit more than one frequency response per time. In +% case that more than one frequency response is passed as input, they +% are fitted with a set of common poles [1]. The function is based on +% the vector fitting algorithm [2 - 4]. +% +% CALL: +% +% [res,poles,fullpoles,mresp,rdl,mse] = psdzfit(y,f,poles,weight,fitin) +% +% INPUTS: +% +% - y: Is a vector with the power spectrum data. +% - f: Is the frequency vector in Hz. +% - poles: are a set of starting poles. +% - weight: are a set of weights used in the fitting procedure. +% - fitin: is a struct containing fitting options and parameters. fitin +% fields are: +% +% - fitin.fs = fs; input the sampling frequency in Hz (default value +% is 1 Hz). +% +% - fitin.polt = 0; fit without plotting results. [Default]. +% - fitin.plot = 1; plot fit results in loglog scale. +% - fitin.plot = 2; plot fit results in semilogx scale. +% - fitin.plot = 3; plot fit results in semilogy scale. +% - fitin.plot = 4; plot fit results in linear xy scale. +% +% - fitin.ploth = #; a plot handle to define the figure target for +% plotting. Default 1. +% +% OUTPUT: +% +% - res: vector of all residues. +% - poles: vector of causal poles. +% - fullpoles: complete vector of poles. +% - mresp: frequency response of the fitted model. +% - rdl: residuals y - mresp. +% - mse: normalized men squared error +% +% EXAMPLES: +% +% - Fit on a single transfer function: +% +% INPUT +% y is a (Nx1) or (1xN) vector +% f is a (Nx1) or (1xN) vector +% poles is a (Npx1) or (1xNp) vector +% weight is a (Nx1) or (1xN) vector +% +% OUTPUT +% res is a (2*Npx1) vector +% poles is a (Npx1) vector +% fullpoles is a (2*Npx1) vector +% mresp is a (Nx1) vector +% rdl is a (Nx1) vector +% mse is a constant +% +% - Fit Nt transfer function at the same time: +% +% INPUT +% y is a (NxNt) or (NtxN) vector +% f is a (Nx1) or (1xN) vector +% poles is a (Npx1) or (1xNp) vector +% weight is a (NxNt) or (NtxN) vector +% +% OUTPUT +% res is a (2*NpxNt) vector +% poles is a (Npx1) vector +% fullpoles is a (2*NpxNt) vector +% mresp is a (NxNt) vector +% rdl is a (NxNt) vector +% mse is a (1xNt) vector +% +% REFERENCES: +% +% [1] +% [2] B. Gustavsen and A. Semlyen, "Rational approximation of frequency +% domain responses by Vector Fitting", IEEE Trans. Power Delivery +% vol. 14, no. 3, pp. 1052-1061, July 1999. +% [3] B. Gustavsen, "Improving the Pole Relocating Properties of Vector +% Fitting", IEEE Trans. Power Delivery vol. 21, no. 3, pp. +% 1587-1592, July 2006. +% [4] Y. S. Mekonnen and J. E. Schutt-Aine, "Fast broadband +% macromodeling technique of sampled time/frequency data using +% z-domain vector-fitting method", Electronic Components and +% Technology Conference, 2008. ECTC 2008. 58th 27-30 May 2008 pp. +% 1231 - 1235. +% +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% HISTORY: 05-05-2009 L Ferraioli +% Creation +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% VERSION: '$Id: psdzfit.m,v 1.1 2009/05/08 13:46:56 luigi Exp $'; +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [res,poles,fullpoles,mresp,rdl,mse] = psdzfit(y,f,poles,weight,fitin) + + warning off all + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Collecting inputs + + % Default input struct + defaultparams = struct('fs',1, 'plot',0, 'ploth',1); + + names = {'fs','plot','ploth'}; + + % collecting input and default params + if ~isempty(fitin) + for jj=1:length(names) + if isfield(fitin, names(jj)) && ~isempty(fitin.(names{1,jj})) + defaultparams.(names{1,jj}) = fitin.(names{1,jj}); + end + end + end + + fs = defaultparams.fs; % sampling frequency + plotting = defaultparams.plot; % set to 1 if plotting is required + plth = defaultparams.ploth; % set the figure target + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Inputs in row vectors + + [a,b] = size(y); + if a > b % shifting to row + y = y.'; + end + + [a,b] = size(f); + if a > b % shifting to row + f = f.'; + end + + [a,b] = size(poles); + if a > b % shifting to row + poles = poles.'; + end + + clear w + w = weight; + [a,b] = size(w); + if a > b % shifting to row + w = w.'; + end + + N = length(poles); % Model order + + % definition of z + z = cos(2.*pi.*f./fs)+1i.*sin(2.*pi.*f./fs); + + Nz = length(z); + + [Nc,Ny] = size(y); + if Ny ~= Nz + error(' Number of data points different from number of frequency points! ') + end + + %Tolerances used by relaxed version of vector fitting + TOLlow=1e-8; + TOLhigh=1e8; + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Marking complex and real poles + + % cindex = 1; pole is complex, next conjugate pole is marked with cindex + % = 2. cindex = 0; pole is real + cindex=zeros(1,N); + for m=1:N + if imag(poles(m))~=0 + if m==1 + cindex(m)=1; + else + if cindex(m-1)==0 || cindex(m-1)==2 + cindex(m)=1; cindex(m+1)=2; + else + cindex(m)=2; + end + end + end + end + ipoles = 1./poles; + effpoles = [poles ipoles]; + ddpol = 1./(poles.*poles); + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Augmented problem + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + + % Matrix initialinzation + BA = zeros(Nc*Nz+1,1); + Ak=zeros(Nz,N+1); + AA=zeros(Nz*Nc+1,N*Nc+N+1); + nf = zeros(1,Nc*N+N+1); % Normalization factor + + % Defining Ak + for jj = 1:N + if cindex(jj) == 1 % conjugate complex couple of poles + Ak(:,jj) = 1./(z-poles(jj)) + 1./(z-conj(poles(jj))) - ddpol(jj)./(z-ipoles(jj)) - conj(ddpol(jj))./(z-conj(ipoles(jj))); + Ak(:,jj+1) = 1i./(z-poles(jj)) - 1i./(z-conj(poles(jj))) - 1i.*ddpol(jj)./(z-ipoles(jj)) + 1i.*conj(ddpol(jj))./(z-conj(ipoles(jj))); + elseif cindex(jj) == 0 % real pole + Ak(:,jj) = 1./(z-poles(jj)) - ddpol(jj)./(z-ipoles(jj)); + end + end + + Ak(1:Nz,N+1) = 1; + + % Scaling factor + sc = 0; + for mm = 1:Nc + sc = sc + (norm(w(mm,:).*y(mm,:)))^2; + end + sc=sqrt(sc)/Nz; + + for nn = 1:Nc + + wg = w(nn,:).'; % Weights + + ida=(nn-1)*Nz+1; + idb=nn*Nz; + idc=(nn-1)*N+1; + + for mm =1:N % Diagonal blocks + AA(ida:idb,idc-1+mm) = wg.*Ak(1:Nz,mm); + end + for mm =1:N+1 % Last right blocks + AA(ida:idb,Nc*N+mm) = -wg.*(Ak(1:Nz,mm).*y(nn,1:Nz).'); + end + + end + + % setting the last row of AA and BA for the relaxion condition + for qq = 1:N+1 + AA(Nc*Nz+1,Nc*N+qq) = real(sc*sum(Ak(:,qq))); + end + + AA = [real(AA);imag(AA)]; + + % Last element of the solution vector + BA(Nc*Nz+1) = Nz*sc; + + xBA = real(BA); + xxBA = imag(BA); + + Nrow = Nz*Nc+1; + + BA = zeros(2*Nrow,1); + + BA(1:Nrow,1) = xBA; + BA(Nrow+1:2*Nrow,1) = xxBA; + + % Normalization factor + % nf = zeros(2*N+dl+1,1); + for pp = 1:length(AA(1,:)) + nf(pp) = norm(AA(:,pp),2); % Euclidean norm + AA(:,pp) = AA(:,pp)./nf(pp); % Normalization + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Solving augmented problem + +% XA = pinv(AA)*BA; + % XA = inv((AA.')*AA)*(AA.')*BA; + + % XA = AA.'*AA\AA.'*BA; + + XA = AA\BA; + + XA = XA./nf.'; % renormalization + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Checking the tolerance + + if abs(XA(end))<TOLlow || abs(XA(end))>TOLhigh + + if XA(end)==0 + Dnew=1; + elseif abs(XA(end))<TOLlow + Dnew=sign(XA(end))*TOLlow; + elseif abs(XA(end))>TOLhigh + Dnew=sign(XA(end))*TOLhigh; + end + + for pp = 1:length(AA(1,:)) + AA(:,pp) = AA(:,pp).*nf(pp); %removing previous scaling + end + + ind=length(AA(:,1))/2; %index to additional row related to relaxation + + AA(ind,:)=[]; % removing relaxation term + + BA=-Dnew*AA(:,end); %new right side + + AA(:,end)=[]; + + nf(end)=[]; + + for pp = 1:length(AA(1,:)) + nf(pp) = norm(AA(:,pp),2); % Euclidean norm + AA(:,pp) = AA(:,pp)./nf(pp); % Normalization + end + + % XA=(AA.'*AA)\(AA.'*BA); % using normal equation + + XA=AA\BA; + + XA = XA./nf.'; % renormalization + + XA=[XA;Dnew]; + + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Finding zeros of sigma + + lsr = XA(N*Nc+1:N*Nc+N,1); % collect the least square results + + D = XA(end); % direct term of sigma + + CPOLES = diag(effpoles); + B = ones(2*N,1); + C = zeros(1,2*N); +% C = lsr.'; + res = zeros(2*N,1); + % Real poles have real residues, complex poles have comples residues + + for tt = 1:N + if cindex(tt) == 1 % conjugate complex couple of poles + res(tt,1) = lsr(tt)+1i*lsr(tt+1); + res(tt+1,1) = lsr(tt)-1i*lsr(tt+1); + res(N+tt,1) = -1*(lsr(tt)+1i*lsr(tt+1))*ddpol(tt); + res(N+tt+1,1) = -1*(lsr(tt)-1i*lsr(tt+1))*conj(ddpol(tt)); + elseif cindex(tt) == 0 % real pole + res(tt,1) = lsr(tt); + res(N+tt,1) = -1*lsr(tt)*ddpol(tt); + end + end + + + for kk = 1:N + if cindex(kk) == 1 + CPOLES(kk,kk)=real(effpoles(kk)); + CPOLES(kk,kk+1)=imag(effpoles(kk)); + CPOLES(kk+1,kk)=-1*imag(effpoles(kk)); + CPOLES(kk+1,kk+1)=real(effpoles(kk)); + B(kk,1) = 2; + B(kk+1,1) = 0; + C(1,kk) = real(res(kk,1)); + C(1,kk+1) = imag(res(kk,1)); + + CPOLES(N+kk,N+kk)=real(effpoles(N+kk)); + CPOLES(N+kk,N+kk+1)=imag(effpoles(N+kk)); + CPOLES(N+kk+1,N+kk)=-1*imag(effpoles(N+kk)); + CPOLES(N+kk+1,N+kk+1)=real(effpoles(N+kk)); + B(N+kk,1) = 2; + B(N+kk+1,1) = 0; + C(1,N+kk) = real(res(N+kk,1)); + C(1,N+kk+1) = imag(res(N+kk,1)); + elseif cindex(kk) == 0 % real pole + C(1,kk) = res(kk,1); + C(1,N+kk) = res(N+kk,1); + end + end + + H = CPOLES-B*C/D; + + % avoiding NaN and inf + idnan = isnan(H); + if any(any(idnan)) + H(idnan) = 1; + end + idinf = isinf(H); + if any(any(idinf)) + H(idinf) = 1; + end + + szeros=eig(H); + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % separating causal from anticausal poles + unst = abs(szeros) > 1; + stab = abs(szeros) <= 1; + unzeros = szeros(unst); + stzeros = szeros(stab); + + stzeros = sort(stzeros); + N = length(stzeros); + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Separating complex poles from real poles and ordering + + rnpoles = []; + inpoles = []; + for tt = 1:N + if imag(stzeros(tt)) == 0 + % collecting real poles + rnpoles = [rnpoles; stzeros(tt)]; + else + % collecting complex poles + inpoles = [inpoles; stzeros(tt)]; + end + end + + % Sorting complex poles in order to have them in the expected order a+jb + % and a-jb a>0 b>0 + inpoles = sort(inpoles); + npoles = [rnpoles;inpoles]; + npoles = npoles - 2.*1i.*imag(npoles); + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Marking complex and real poles + + cindex=zeros(N,1); + for m=1:N + if imag(npoles(m))~=0 + if m==1 + cindex(m)=1; + else + if cindex(m-1)==0 || cindex(m-1)==2 + cindex(m)=1; cindex(m+1)=2; + else + cindex(m)=2; + end + end + end + end + + inpoles = 1./npoles; + effnpoles = [npoles;inpoles]; + ddpol = 1./(npoles.*npoles); + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Direct problem + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + + % Matrix initialinzation + nB(1:Nz,1:Nc) = real(w.*y).'; + nB(Nz+1:2*Nz,1:Nc) = imag(w.*y).'; + + B = zeros(2*Nz,1); + nAD = zeros(Nz,N); + AD = zeros(2*Nz,N); + Ak = zeros(Nz,N); + + for jj = 1:N + if cindex(jj) == 1 % conjugate complex couple of poles + Ak(:,jj) = 1./(z-npoles(jj)) + 1./(z-conj(npoles(jj))) - ddpol(jj)./(z-inpoles(jj)) - conj(ddpol(jj))./(z-conj(inpoles(jj))); + Ak(:,jj+1) = 1i./(z-npoles(jj)) - 1i./(z-conj(npoles(jj))) - 1i.*ddpol(jj)./(z-inpoles(jj)) + 1i.*conj(ddpol(jj))./(z-conj(inpoles(jj))); + elseif cindex(jj) == 0 % real pole + Ak(:,jj) = 1./(z-npoles(jj)) - ddpol(jj)./(z-inpoles(jj)); + end + end + + XX = zeros(Nc,N); + for nn = 1:Nc + + % Defining AD + for m=1:N + nAD(1:Nz,m) = w(nn,:).'.*Ak(1:Nz,m); + end + + B(1:2*Nz,1) = nB(1:2*Nz,nn); + + AD(1:Nz,:) = real(nAD); + AD(Nz+1:2*Nz,:) = imag(nAD); + + % Normalization factor + nf = zeros(N,1); + for pp = 1:N + nf(pp,1) = norm(AD(:,pp),2); % Euclidean norm + AD(:,pp) = AD(:,pp)./nf(pp,1); % Normalization + end + + % Solving direct problem + + % XD = inv((AD.')*AD)*(AD.')*B; + % XD = AD.'*AD\AD.'*B; +% XD = pinv(AD)*B; + XD = AD\B; + + XD = XD./nf; % Renormalization + XX(nn,1:N) = XD(1:N).'; + + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Final residues and poles of f + + lsr = XX(:,1:N); + + clear res + + res = zeros(2*N,Nc); + % Real poles have real residues, complex poles have comples residues + for nn = 1:Nc + for tt = 1:N + if cindex(tt) == 1 % conjugate complex couple of poles + res(tt,nn) = lsr(nn,tt)+1i*lsr(nn,tt+1); + res(tt+1,nn) = lsr(nn,tt)-1i*lsr(nn,tt+1); + res(N+tt,nn) = -1*(lsr(tt)+1i*lsr(tt+1))*ddpol(tt); + res(N+tt+1,nn) = -1*(lsr(tt)-1i*lsr(tt+1))*conj(ddpol(tt)); + elseif cindex(tt) == 0 % real pole + res(tt,nn) = lsr(nn,tt); + res(N+tt,nn) = -1*lsr(nn,tt)*ddpol(tt); + end + end + end + + + poles = npoles; + fullpoles = effnpoles; + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Calculating responses and residuals + + mresp = zeros(Nz,Nc); + rdl = zeros(Nz,Nc); + yr = zeros(Nz,Nc); + mse = zeros(1,Nc); + + for nn = 1:Nc + % freq resp of the fit model + r = res(:,nn); + p = effnpoles; + + Nf = length(f); + N = length(p); + + rsp = zeros(Nf,1); + for ii = 1:Nf + for jj = 1:N + rsptemp = r(jj)/(z(ii)-p(jj)); + rsp(ii) = rsp(ii) + rsptemp; + end + end + + % Model response + mresp(:,nn) = rsp; + + % Residual + yr(:,nn) = y(nn,:).'; + rdl(:,nn) = yr(:,nn) - rsp; + + % RMS error +% rmse(:,nn) = sqrt(sum((abs(rdl(:,nn)./yr(:,nn)).^2))/(Nf-N)); + + % Chi Square or mean squared error + % Note that this error is normalized to the input data in order to + % comparable between different sets of data + mse(:,nn) = sum((rdl(:,nn)./yr(:,nn)).*conj((rdl(:,nn)./yr(:,nn))))/(Nf-N); + + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Plotting response + nf = f./fs; + + switch plotting + + case 0 + % No plot + + case 1 + % LogLog plot for absolute value + figure(plth) + subplot(2,1,1); + p1 = loglog(nf,abs(yr),'k'); + hold on + p2 = loglog(nf,abs(mresp),'r'); + p3 = loglog(nf,abs(rdl),'b'); + xlabel('Normalized Frequency [f/fs]') + ylabel('Amplitude') + legend([p1(1) p2(1) p3(1)],'Original', 'PSDZFIT','Residual') + hold off + + subplot(2,1,2); + p4 = semilogx(nf,(180/pi).*unwrap(angle(yr)),'k'); + hold on + p5 = semilogx(nf,(180/pi).*unwrap(angle(mresp)),'r'); + xlabel('Normalized Frequency [f/fs]') + ylabel('Phase [Deg]') + legend([p4(1) p5(1)],'Original', 'PSDZFIT') + hold off + + case 2 + % Semilogx plot for absolute value + figure(plth) + subplot(2,1,1); + p1 = semilogx(nf,abs(yr),'k'); + hold on + p2 = semilogx(nf,abs(mresp),'r'); + p3 = semilogx(nf,abs(rdl),'b'); + xlabel('Normalized Frequency [f/fs]') + ylabel('Amplitude') + legend([p1(1) p2(1) p3(1)],'Original', 'PSDZFIT','Residual') + hold off + + subplot(2,1,2); + p4 = semilogx(nf,(180/pi).*unwrap(angle(yr)),'k'); + hold on + p5 = semilogx(nf,(180/pi).*unwrap(angle(mresp)),'r'); + xlabel('Normalized Frequency [f/fs]') + ylabel('Phase [Deg]') + legend([p4(1) p5(1)],'Original', 'PSDZFIT') + hold off + + case 3 + % Semilogy plot for absolute value + figure(plth) + subplot(2,1,1); + p1 = semilogy(nf,abs(yr),'k'); + hold on + p2 = semilogy(nf,abs(mresp),'r'); + p3 = semilogy(nf,abs(rdl),'b'); + xlabel('Normalized Frequency [f/fs]') + ylabel('Amplitude') + legend([p1(1) p2(1) p3(1)],'Original', 'PSDZFIT','Residual') + hold off + + subplot(2,1,2); + p4 = semilogy(nf,(180/pi).*unwrap(angle(yr)),'k'); + hold on + p5 = semilogy(nf,(180/pi).*unwrap(angle(mresp)),'r'); + xlabel('Normalized Frequency [f/fs]') + ylabel('Phase [Deg]') + legend([p4(1) p5(1)],'Original', 'PSDZFIT') + hold off + + case 4 + % Linear plot for absolute value + figure(plth) + subplot(2,1,1); + p1 = plot(nf,abs(yr),'k'); + hold on + p2 = plot(nf,abs(mresp),'r'); + p3 = plot(nf,abs(rdl),'b'); + xlabel('Normalized Frequency [f/fs]') + ylabel('Amplitude') + legend([p1(1) p2(1) p3(1)],'Original', 'PSDZFIT','Residual') + hold off + + subplot(2,1,2); + p4 = plot(nf,(180/pi).*unwrap(angle(yr)),'k'); + hold on + p5 = plot(nf,(180/pi).*unwrap(angle(mresp)),'r'); + xlabel('Normalized Frequency [f/fs]') + ylabel('Phase [Deg]') + legend([p4(1) p5(1)],'Original', 'PSDZFIT') + hold off + + end \ No newline at end of file