专题软件开发实践报告(3)

s3=str2double(get(handles.edit4,'String'))%从文本框中获得数据赋值给s3 h = 1/s1;

x = [h/2:h:1-h/2]';

% Compute matrix K corresponding to convolution with Gaussian kernel.

kernel = (1/sqrt(pi)/s2) * exp(-(x-h/2).^2/s2^2);

K = toeplitz(kernel)*h;

% Set up true solution f_true and data d = K*f_true + error.

f_true = .75*(.1<x&x<.25) + .25*(.3<x&x<.32) + (.5<x&x<1).*sin(2*pi*x).^4;

Kf = K*f_true;

eta = s3/100 * norm(Kf) * randn(s1,1)/sqrt(s1);

d = Kf + eta;

% Display the data.

% figure(2)

plot(x,f_true,'-', x,d,'o',x,Kf,'--')

xlabel('x axis')

axes(handles.axes1);%把图形画到指定的位置

% --- Executes on button press in pushbutton4.

function pushbutton4_Callback(hObject, eventdata, handles)

% hObject handle to pushbutton4 (see GCBO)

% eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) s1=str2double(get(handles.edit2,'String'))

s2=str2double(get(handles.edit3,'String'))

s3=str2double(get(handles.edit4,'String'))

% Set up grid.

h = 1/s1;

x = [h/2:h:1-h/2]';

% Compute matrix K corresponding to convolution with Gaussian kernel. kernel = (1/sqrt(pi)/s2) * exp(-(x-h/2).^2/s2^2);

K = toeplitz(kernel)*h;

% figure(1)

mesh(K)

title('Mesh Plot Representation of Matrix K')

axes(handles.axes3);