function [param,H,L0,ABCD,x] = designLCBP(n,OSR,opt,Hinf,f0,t,form,x0,dbg)%[param,H,L0,ABCD,x]=designLCBP(n=3,OSR=64,opt=2,Hinf=1.6,f0=1/4,t=[0 1],form='FB',x0,dbg=0)%Design an LC modulator of order 2*n with center frequency f0.%The feedback waveform is a rectangular pulse from t(1) to t(2).%Arguments% n	The number of LC tanks.% OSR	The oversampling ratio.% opt	A flag for NTF zero optimization. See synthesizeNTF.% Hinf	The target out-of-band gain of the NTF.% f0	The center frequency of the modulator, normalized to fs.% t	A 2-element vector containing the (normalized) feedback pulse edge times.% form	The modulator topology. One of 'FB', 'FF', 'FFR' or 'GEN'.% x0	An initial guess at the parameter vector for the optimizer.% dbg	A flag for enabling debugging/progress report output.%%Output% param	A struct containing the (n, OSR, Hinf, f0, t and form) arguments%   plus the following fields:%   l   The inductances in each tank.%   c	The capacitances in each tank.%   gu	The transconductance from the u input to each of the tanks.%	The final term is the voltage gain from u to the comparator input.%	(1 by n+1)%   gv	The transconductance from the v output to each of the tanks. (1 by n)%   gw	The inter-stage transconductances. (1 by n-1)%   gx	The gains from the top of each tank resistor to the comparator. (1 by n)%   rx	The resistances inserted between the output of each interstage %	transconductance and top of each tank. Note that r(1) is not used.%	(1 by n)%% H	The noise transfer function of the modulator, taking into account%	the post-design quantizer gain.% L0	A description of the open-loop TF from u to v, for use with evalTFP().% ABCD	The state-space representation of the discrete-time equivalent.% Handle the input argumentsparameters = {'n';'OSR';'opt';'Hinf';'f0';'t';'form';'x0';'dbg'};defaults = { 3 64 2 1.6 0.25 [0 1] 'FB' NaN 0 };for i=1:length(defaults)    parameter = char(parameters(i));    if i>nargin | ( eval(['isnumeric(' parameter ') '])  &  ...     eval(['any(isnan(' parameter ')) | isempty(' parameter ') ']) )        eval([parameter '=defaults{i};'])    endendparam.n = n;	param.OSR = OSR;	param.Hinf = Hinf;param.f0 = f0;	param.t = t;		param.form = form;% Compute the resonant frequencies for the LC tanks % and the L and C values.if opt    w = 2*pi*(f0 + 0.25/OSR*ds_optzeros(n,opt)');else    w = 2*pi*f0*ones(1,n);endparam.l = (1./w);	param.c = (1./w);	% Impedance scaling is possible.% Find values for the parameters that yield a stable system.% ?? Could some control theory help here ??if isnan(x0)    x = [2:n+1];elseif length(x0) ~= n    error('Initial guess (x0) has the wrong number of parameters.');else    x = x0;endif exist('fmincon','file')==2	% Latest version of Optimization Toolbox    [param,H,L0,ABCD,x] = designLCBP6(n,OSR,opt,Hinf,f0,t,form,x0,dbg);elseif exist('constr','file')==2	% Older version of Optimization Toolbox    if dbg	fprintf(1, 'Iterations for initial pole placement:\n');    end    options = foptions;    options(2) = 0.001;	% x tolerance    options(3) = 1;	% f tolerance    options(14) = 1000;	% Maximum number of iterations    x = constr('LCObj1',x,options,[],[],[],param,0.97,dbg);    H = LCoptparam2tf(x,param);    rmax = max(abs(H.p{:}));    if rmax>0.97	% Failure to converge!	fprintf(2,'Unable to find parameter values which stabilize the system.\n');	return    end    % Do the main optimization for the feedback parameters.    if dbg>1	options(1) = 1; 	% Extra debugging info    end    if dbg	fprintf(1, '\nParameter Optimization:\n');    end    options(2)  = 1e-4;	% x tolerance    options(3)  = 0.5;	% f tolerance    options(4)  = 0.01;	% constraint tolerance    %options(13) = 1;	% Number of equality constraints    options(14) = 1000;	% Maximum number of iterations.    options(16) = 1e-4;	% Minimum dx for finite difference gradients    options(17) = 1e-2;	% Maximum dx for finite difference gradients    options(18) = .01;	% Step length. (This doesn't prevent large steps!)    % I have used minimax() and constr() below    [x,options] = minimax('LCObj',x,options,[],[],[],param,dbg);    [H L0 ABCD param] = LCoptparam2tf(x,param);    % Uncomment the following line to take into account the quantizer gain     % before returning results and doing the plots    %[H L0 ABCD k] = LCparam2tf(param,0);    % Uncomment the following lines to yield parameters corresponding to k=1    %param.gu = k*param.gu; param.gv = k*param.gv;    %ABCD(2*n+1,:) = ABCD(2*n+1,:)/k;    %ABCD(:, 2*n+[1 2]) = ABCD(:, 2*n+[1 2]) *k;    % Now fix up the inputs for 0dB gain at f0.    gain_f0 = abs(evalTFP(L0,H,f0));     param.gu = param.gu/gain_f0; L0.k = L0.k/gain_f0;    ABCD(:,2*n+1) = ABCD(:,2*n+1)/gain_f0;    if strcmp(form,'FF') | strcmp(form,'FFR')	param.gu(n+1) =1;		% For the flattest STF    end    if dbg	LCplotTF(H,L0,param);    endelse    fprintf(1, 'Sorry, designLCBP needs the optimization toolbox.\n');endreturn