> For the complete documentation index, see [llms.txt](https://alfredo-reyes-montero.gitbook.io/soft-computing/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://alfredo-reyes-montero.gitbook.io/soft-computing/applications/matlab/perceptron/little-red-riding-hood.md).

# Little Red Riding Hood

This example try to show the principle of the perceptron algorithm. The objective of this application is to determine in based of some characteristics which person you are taking about.

This is the code of the application, some code is not mention because only help us to define de GUI, but everything you can watch on GitHub.

This method is in charge to execute the perceptron algorithm, read the input and the output that we previously select con the ui, and a training base array to compare and could resolve which character we selected.

```
% --- Executes on button press in pushbutton7.
function pushbutton7_Callback(hObject, eventdata, handles)
% hObject    handle to pushbutton7 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)
% aqui se entrena al perceptron
global W1;
global W2;
set(handles.edit3,'String','Procesando');
coefApre = rand;
input = [ 1, 1, 1, 0, 0, 0;
    1, 0, 0, 1, 0, 1;
    0, 0, 1, 0, 1, 1];
output = [1, 1, 1, 0, 0, 0, 0;
    0, 0, 0, 1, 1, 0, 1;
    0, 0, 0, 1, 0, 1, 1];
out1 = [0, 0, 0, 0, 0, 0, 0];
out2 = [0, 0, 0, 0, 0, 0, 0];
E = [0, 0, 0, 0, 0, 0, 0];
A = [0, 0, 0, 0, 0, 0, 0];
W1 = rand(6,7);
W2 = rand(7);
error = 1;
while error > 0.08%cada ciclo es una etapa
    error = 0;
    for e =1:1:3% cada ciclo es el calculo de una entrada
        %calcula salidas de capa oculta
        for i = 1:1:7
            in = input(e,:) * W1(:,i);
            out1(i) = 1 / (1 + exp(-1*in));
        end
        %calcula salida de utlima capa
        for i = 1:1:7
            in = out1 * W2(:,i);
            out2(i) = 1 / (1 + exp(-1*in));
        end
        %AJUSTE DE PESOS
        %pesos de la ultima capa
        for i = 1:1:7
            E(i) = output(e,i) - out2(i);       %error
        end
        errorSuma = 0;
        for i = 1:1:7
            errorSuma = errorSuma + abs(E(i));       %error
        end
        if error < errorSuma;
            error = errorSuma;
        end
        for i = 1:1:7
            A(i) = E(i) * out2(i) * (1 - out2(i));  %calculo de retropropagacion
            for j = 1:1:7
                W2(j,i) = W2(j,i) + (coefApre * out1(j) * A(i));
            end
        end
        %pesos para la capa oculta
        for i = 1:1:7
            delta = 0;
            for k = 1:1:7
                delta = delta + W2(k,i)*A(k);
            end
            delta = out1(i) * (1 - out1(i)) * (delta);    %calculo de retropropagacion
            for j = 1:1:6
                W1(j,i) = W1(j,i) + (coefApre * input(e,j) * delta);
            end
        end
    end
end
set(handles.edit3,'String','Finalizo Entrenamiento');
```

This method help us to print base on the output the photo of the character, and also some behavior of them.

```
% --- Executes on button press in pushbutton8.
function pushbutton8_Callback(hObject, eventdata, handles)
% hObject    handle to pushbutton8 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)
%aqui evalua a las entradas
global W1;
global W2;
set(handles.edit1,'String','');

input = [0, 0, 0, 0, 0, 0];
if(strcmp(get(handles.pushbutton1,'String'),'SI'))
    input(1) = 1;
else
    input(1) = 0;
end
if(strcmp(get(handles.pushbutton2,'String'),'SI'))
    input(2) = 1;
else
    input(2) = 0;
end
if(strcmp(get(handles.pushbutton3,'String'),'SI'))
    input(3) = 1;
else
    input(3) = 0;
end
if(strcmp(get(handles.pushbutton4,'String'),'SI'))
    input(4) = 1;
else
    input(4) = 0;
end
if(strcmp(get(handles.pushbutton5,'String'),'SI'))
    input(5) = 1;
else
    input(5) = 0;
end
if(strcmp(get(handles.pushbutton6,'String'),'SI'))
    input(6) = 1;
else
    input(6) = 0;
end
out1 = [0, 0, 0, 0, 0, 0, 0];
out2 = [0, 0, 0, 0, 0, 0, 0];
for i = 1:1:7
    in = input * W1(:,i);
    out1(i) = 1 / (1 + exp(-1*in));
end
for i = 1:1:7
    in = out1 * W2(:,i);
    out2(i) = round(1 / (1 + exp(-1*in)));
end
if(out2(1)==1)
    set(handles.text9,'Visible','on');
else
    set(handles.text9,'Visible','off');
end
if(out2(2)==1)
    set(handles.text10,'Visible','on');
else
    set(handles.text10,'Visible','off');
end
if(out2(3)==1)
    set(handles.text11,'Visible','on');
else
    set(handles.text11,'Visible','off');
end
if(out2(4)==1)
    set(handles.text12,'Visible','on');
else
    set(handles.text12,'Visible','off');
end
if(out2(5)==1)
    set(handles.text13,'Visible','on');
else
    set(handles.text13,'Visible','off');
end
if(out2(6)==1)
    set(handles.text14,'Visible','on');
else
    set(handles.text14,'Visible','off');
end
if(out2(7)==1)
    set(handles.text15,'Visible','on');
else
    set(handles.text15,'Visible','off');
end
lobo = [1, 1, 1, 0, 0, 0, 0];
abuelita = [0, 0, 0, 1, 1, 0, 1];
lenador = [0, 0, 0, 1, 0, 1, 1];

axes(handles.axes1)

if out2 == lobo
    set(handles.edit1,'String','Es el Lobo');
    imshow('lobo.png')
end
if out2 == abuelita
    set(handles.edit1,'String','Es la Abuelita');
    imshow('abuelita.jpg')
end
if out2 == lenador
    set(handles.edit1,'String','Es el Lenador');
    imshow('lenador.jpg')
end
```


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://alfredo-reyes-montero.gitbook.io/soft-computing/applications/matlab/perceptron/little-red-riding-hood.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.