function h=holder(tfr,f,n1,n2,t,pl)%HOLDER	Estimate the Holder exponent through an affine TFR.%	H=HOLDER(TFR,F,N1,N2,T) estimates the Holder exponent of a %	function through an affine time-frequency representation of it, %	and plots the frequency marginal and the regression line.  %%	TFR : affine time-frequency representation.  %	F   : frequency values of the spectral analysis. %	N1  : indice of the  minimum frequency for the linear regression.  %                                         (default : 1).%	N2  : indice of the  maximum frequency for the linear regression.  %                                         (default : length(F)).%	T : time vector. If T is omitted, the function returns the%	    global estimate of the Holder exponent. Otherwise, it%	    returns the local estimates H(T) at the instants specified%	    in T.  %	H : output value (if T omitted) or vector (otherwise) containing%	    the Holder estimate(s).%%	Example :%	 S=altes(128); [TFR,T,F]=tfrscalo(S,1:128,8);%	 H=holder(TFR,F,1,length(F));%	P. Goncalves, October 1995%	Copyright (c) 1995 Rice University%%	------------------- CONFIDENTIAL PROGRAM -------------------- %	This program can not be used without the authorization of its%	author(s). For any comment or bug report, please send e-mail to %	f.auger@ieee.org clg;tfr = abs(tfr) ;if nargin<2, error('There must be at least 2 input parameters');elseif nargin==2, n1=1; n2=length(f);elseif nargin==3, n2=length(f);endif nargin<=5, pl=1;else pl=0;endif nargin <= 4  fmarg = mean(tfr.').' ;  if pl, plot(log(f),log(fmarg)) , hold on; end;  p = polyfit(log(f(n1:n2)),log(fmarg(n1:n2)),1) ;  drt = p(1)*log(f)+p(2) ;  if pl,   plot(log(f),drt,'--g') ;    legend('Frequency marginal','Regression line');   plot(log(f([n1 n2])),log(fmarg([n1 n2])),'+r') ;   xticklabels = round(logspace(log10(min(f)),log10(max(f)),4)*1000)./1000 ;   set(gca,'XTick',log(xticklabels)) ;    xlabel('frequency (logarithmically spaced)') ;   hold off ;  end  h = (-p(1)-1)/2 ;else  if length(t) == 1    if pl, plot(log(f),log(tfr(:,t))) ; hold on; end    p = polyfit(log(f(n1:n2)),log(tfr(n1:n2,t)),1) ;    drt = p(1)*log(f)+p(2) ;    if pl,      plot(log(f),drt,'--g') ;     legend('Frequency marginal','Regression line');     plot(log(f([n1 n2])),log(tfr([n1 n2],t)),'+r') ;     xticklabels = round(logspace(log10(min(f)),log10(max(f)),4)*1000)./1000 ;     set(gca,'XTick',log(xticklabels)) ;      xlabel('frequency (logarithmically spaced)') ;     hold off ;    end    h = (-p(1)-1)/2 ;  elseif length(t) > 1     [yt,xt] = size(t) ; if yt>xt, t = t.' ; end ;    j = 1 ;    for k = t,      p = polyfit(log(f(n1:n2)),log(tfr(n1:n2,k)),1) ;      h(j) = (-p(1)-1)/2 ; j = j + 1 ;    end    if pl,      plot(t,h) ;grid     title('Holder estimates at time instants T');    end  end,end