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author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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date | Mon, 05 Dec 2011 16:20:06 +0100 |
parents | f0afece42f48 |
children | bc767aaa99a8 |
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% MATH helper class for math utility functions. % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % DESCRIPTION: MATH is a helper class for math utility functions. % % To see the available static methods, call % % >> methods utils.math % % HISTORY: M Hewitson 26-05-08 % Creation % % VERSION: $Id: math.m,v 1.77 2011/10/07 08:19:06 miquel Exp $ % % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% classdef math %------------------------------------------------ %--------- Declaration of Static methods -------- %------------------------------------------------ methods (Static) %------------------------------------------------------------- % List other methods %------------------------------------------------------------- varargout = intfact(varargin); % Compute two integers P and Q varargout = cpf(varargin) varargout = lp2z(varargin) p = phase(resp) r = deg2rad(deg, min, sec) [G,ri] = fq2ri(f0, Q) ri = fq2ri2(f0, Q) [f0, q] = ri2fq(c) deg = unwrapdeg(phase) val = rand(r1, r2) [res,poles,dterm,mresp,rdl,rmse] = autocfit(y,f,params) [res,poles,dterm,mresp,rdl,rmse] = autodfit(y,f,fs,params) [res,poles,dterm,mresp,rdl] = ctfit(y,f,poles,weight,fitin) [res,poles,dterm,mresp,rdl] = dtfit(y,f,poles,weight,fitin) [res,poles,dterm,mresp,rdl,rmse] = vcfit(y,f,poles,weight,fitin) [res,poles,dterm,mresp,rdl,rmse] = vdfit(y,f,poles,weight,fitin) [h11,h12,h21,h22] = eigpsd(psd1,csd,psd2,varargin) [h11,h12,h21,h22] = eigcsd(csd11,csd12,csd21,csd22,varargin) varargout = pfallps(ir,ip,id,mresp,f,varargin) [nr,np,nd,nmresp] = pfallpsymz(r,p,d,mresp,f,fs) [nr,np,nd,nmresp] = pfallpsyms(r,p,d,f) varargout = pfallpz(ir,ip,id,mresp,f,fs,varargin) varargout = psd2tf(varargin) varargout = psd2wf(varargin) spoles = startpoles(order,f,params) weight = wfun(y,weightparam) [ext,msg] = stopfit(y,rdl,rmse,ctp,lrscond,rmsevar) pfr = pfresp(pfparams) Deriv = fpsder(a, params) zi = iirinit(a,b) sw = spflat(S) out = randelement(arr, N) covmat = jr2cov(J,resid) J = getjacobian(coeff,model,X) h = ndeigcsd(csd,varargin) ostruct = csd2tf(csd,f,params) [res,poles,fullpoles,mresp,rdl,mse] = psdzfit(y,f,poles,weight,fitin) varargout = computepsd(Sxx,Svxx,w,range,nfft,Fs,esttype) res = isequal(varargin) [a,Ca,Corra,Vu,bu,Cbu,Fbu,mse,dof,ppm] = linfitsvd(varargin) [a,Ca,Corra,Vu,bu,Cbu,Fbu,mse,dof,ppm] = linlsqsvd(varargin) Zi = getinitstate(res,poles,S0,varargin) varargout = pfallpz2(ip,mresp,f,fs) ostruct = csd2tf2(csd,f,params) varargout = pfallpsymz2(ip,mresp,f,fs) varargout = pfallpsyms2(ip,mresp,f) varargout = pfallps2(ip,mresp,f) FisMat = fisher_2x2(i1,i2,n,mdl,params,numparams,freqs,N,pl,inNames,outNames) FisMat = fisher_1x1(i1,n,mdl,params,numparams,freqs,N,pl,inNames,outNames) best = diffStepFish(i1,i2,S11,S12,S21,S22,N,meval,params,ngrid,ranges,freqs,inNames,outNames) best = diffStepFish_1x1(i1,S11,N,meval,params,values,ngrid,ranges,freqs,inNames,outNames) loglk = loglikelihood(varargin) loglk = loglikelihood_ssm(varargin) [loglk snr] = loglikelihood_matrix(varargin) snrexp = stnr(tmplt1,tmplt2,out1,out2,InvS11,InvS22,InvS12,InvS21) loglk = loglikelihood_ssm_td(xp,in,out,parnames,model,inNames,outNames,Noise,varargin) loglk = loglikelihood_td(res,noise,varargin) params = fitPrior(prior,nparam,chain,bins) Xt = blwhitenoise(npts,fs,fl,fh) [smpl smplr] = mhsample(model,in,out,nse,cov,number,limit,param,Tc,xi,xo,search,jumps,parplot,dbg_info,inNames,outNames,fpars,anneal,SNR0,DeltaL,inModel,outModel) [A,B,C,D] = pf2ss(res,poles,dterm) [w_i,powers,w_mse,p_mse] = rootmusic(x,p,varargin) [music_data,msg] = music(x,p,varargin) k = getk(z,p,zfg) dc = getdc(z,p,k) [A,B,C,D] = pzmodel2SSMats(pzm) varargout = filtfilt_filterbank(fbk,in) cmat = xCovmat(x,y,varargin) chi2 = chisquare_ssm_td(xp,in,out,parnames,model,inNames,outNames,varargin) [CorrC,SigC] = cov2corr(Covar) Covar = corr2cov(CorrC,SigC) R = Rcovmat(x) smpl = mhsample_td(model,in,out,cov,number,limit,parnames,Tc,xi,xo,search,jumps,parplot,dbg_info,inNames,outNames,inNoise,inNoiseNames,cutbefore,cutafter) Bxy = rjsample(model,in,out,nse,cov,number,limit,param,Tc,xi,xo,search,jumps,parplot,dbg_info,inNames,outNames,inModel,outModel) [Fout,x] = ecdf(y) cVal = SKcriticalvalues(n1,n2,alph) x = Finv(p,n1,n2) p = Fcdf(x,n1,n2) rsp = mtxiirresp(fil,freq,fs,bank) rsp = mtxiirresp2(A,B,freq,fs) rsp = mtxratresp2(A,B,freq) f = getfftfreq(nfft,fs,type) h = cdfplot(y1,y2,ops) h = qqplot(y1,y2,ops) h = ppplot(y1,y2,ops) boxplot(varargin) p = Normcdf(x,mu,sigma) x = Norminv(p,mu,sigma) p = Chi2cdf(x,v) x = Chi2inv(p,v) [H, KSstatistic, criticalValue, pValue] = kstest(y1, y2, alpha, varargin) [test,critValue,pValue] = Ftest(F,dof1,dof2,alpha,twoTailed) test = SFtest(X,Y,alpha,showPlots) s = Skew(x) k = Kurt(x) [rw,s] = crank(w) [rs,pValue,TestRes] = spcorr(y1,y2,alpha) [chi2,g] = chi2(p,data,models,Dmodels,lb,ub) pValue = KSpValue(KSstatistic,n1,n2) R = freqCorr(w,eta,T) varargout = overlapCorr(w,N,navs) Gf = dft(gt,f,T) Sf = computeDftPeriodogram(x,fs,f,order,win,psll) Sf = welchdft(x,fs,f,Ns,olap,navs,order,win,psll) y = unitStep(x); y = heaviside(x); %------------------------------------------------------------- %------------------------------------------------------------- end % End static methods end % END