% Gregory J. Toussaint
% ECE 417 Nonlinear and Adaptive Control
% 26 Oct 98
% Homework Assignment 4
% Problem 16
% Filename:  prob16_a_1.m
%
% Study of Recursive Least Squares Estimation
%

clear
format compact

% Open or create the file to write the LaTeX commands to 
fid = fopen('prob16.tex','a');

% Set up the string variables
HW_Num = '4';
Prob_Num = '16';
Roman = 'i';
Letter = 'a';

% Adjust the plot number
plot_number = 0;
tex_print = 1;   % Zero to not print .tex file, one to print

%
% Solve the homework problem.
%
% Use loops to examine all of the different cases.
%

% keep track of the plot numbers and *.ps files
plot_number = plot_number + 1;

title_str = (['HW ',HW_Num,' Prob ',Prob_Num,' (',Roman,'-',num2str(plot_number),'), G. J. Toussaint']);
print_str = (['prob',Prob_Num,'_',Letter,'_',num2str(plot_number),'.ps']);

% Sample the functions to be plotted to reduce the data
t_new = t(1:10:length(t));
theta_new = theta_hat(:,1:10:size(theta_hat,2));

% Plot the sampled functions
prob16_print(t_new,theta_new,theta_naught,title_str)

% If desired, form the contents of the .tex file
if tex_print
  tex_fig_print(fid,Prob_Num,Roman,Letter,num2str(plot_number),print_str, ...
  u_str,gamma,sigma^2,theta_hat_0);
end;

eval(['print -deps ',print_str])

status = fclose(fid);

Results = [theta_hat(:,size(theta_hat,2)) theta_naught ...
 theta_hat(:,size(theta_hat,2))-theta_naught]

% End of HW 4 Problem 16
% Gregory J. Toussaint