SoloCodigo

Qué tal! Me llamo José Manuel y realizo el PFC sobre redes neuronales. Estoy un poco atascao y sólo haciendo esto, así q a ver si m podeis exar una manilla.

Resulta q tengo q simular el comportamiento de un transistor. Para ello, trabajo sobre una red sencillita, q os adjunto, y he de obtener ciertos pesos y bias de esta red para conseguir cierta función de transferencia entre la entrada y salida. Pues bien, m creo mi red, le meto los valores de entrenamiento medidos en el laboratorio y m salen unos errores mu curiosos. Por ejemplo, conecto la capa 6 con la 4 y al hacer net.LW{6,4}=1, m da un error (dice q la matriz esa debe ser nula. ¿Por qué, si esa conexión sí existe y la denoto con anterioridad en el código?).

Bueno, aquí os mando la red y el código (será una carilla a lo sumo, es sencillito), pa ver si veis algo q yo no veo, q es q llevo dándole vueltas mucho tiempo y lo mismo es algo tan evidente q ni m preocupo de ello. Si podeis, escribirme al correo mejor. Si no, contestad por aki. Un saludo y muchisimas gracias!!

jmanguasp@hotmail.com




******************************************************************
%**Aproximacion de la curva Ids frente a Vgs,Vds (Modelo Angelov)**
%******************************************************************

%********Transitor HEMT modelo foundry ED02AH con W=2*40***********

%************************Con 5 parametros**************************

net=network;                    

net.numInputs=2;                %dos entradas];  %primera entrada conectada a capa 1 y segunda entrada conectada a capas 3 y 5
net.layerConnect(2,1)=1;        %conexiones entre capa (ver red)
net.layerConnect(4,3)=1;
net.layerConnect(6,2)=1;
net.layerConnect(6,4)=1;
net.layerConnect(6,5)=1;
net.outputConnect(6)=1;
net.targetConnect(6)=1;

net.layers{1}.transferFcn='tansig';    %funciones de transferencia de cada capa (ver red)
net.layers{2}.transferFcn='purelin';
net.layers{3}.transferFcn='purelin';
net.layers{4}.transferFcn='purelin';
net.layers{5}.transferFcn='tansig';
net.layers{6}.transferFcn='purelin';
net.layers{6}.netInputFcn='netprod';

net.biasConnect=[1;1;0;1;0;0];  %biases que existen (ver red)

net=init(net);                  %inicializacion de los pesos
net.initFcn='initlay';
net.layers{1}.initFcn='initnw';    
net.layers{2}.initFcn='initnw';
net.layers{3}.initFcn='initnw';
net.layers{4}.initFcn='initnw';
net.layers{5}.initFcn='initnw';
net.layers{6}.initFcn='initnw';

%introduccion valores deseados (P=pareja Vgs,Vds y T=Ids) medidos en laboratorio
P=[[-2 ; 0] [-2 ; 0.1] [-2 ; 0.2] [-2 ; 0.3] [-2 ; 0.4] [-2 ; 0.5] [-2 ; 0.6] [-2 ; 0.7] [-2 ; 0.8] [-2 ; 0.9] [-2 ; 1] [-2 ; 1.1] [-2 ; 1.2] [-2 ; 1.3] [-2 ; 1.4] [-2 ; 1.5] [-2 ; 1.6] [-2 ; 1.7] [-2 ; 1.8] [-2 ; 1.9] [-2 ; 2] [-2 ; 2.1] [-2 ; 2.2] [-2 ; 2.3] [-2 ; 2.4] [-2 ; 2.5] [-2 ; 2.6] [-2 ; 2.7] [-2 ; 2.8] [-2 ; 2.9] [-2 ; 3] [-1.9 ; 0] [-1.9 ; 0.1] [-1.9 ; 0.2] [-1.9 ; 0.3] [-1.9 ; 0.4] [-1.9 ; 0.5] [-1.9 ; 0.6] [-1.9 ; 0.7] [-1.9 ; 0.8] [-1.9 ; 0.9] [-1.9 ; 1] [-1.9 ; 1.1] [-1.9 ; 1.2] [-1.9 ; 1.3] [-1.9 ; 1.4] [-1.9 ; 1.5] [-1.9 ; 1.6] [-1.9 ; 1.7] [-1.9 ; 1.8] [-1.9 ; 1.9] [-1.9 ; 2] [-1.9 ; 2.1] [-1.9 ; 2.2] [-1.9 ; 2.3] [-1.9 ; 2.4] [-1.9 ; 2.5] [-1.9 ; 2.6] [-1.9 ; 2.7] [-1.9 ; 2.8] [-1.9 ; 2.9] [-1.9 ; 3] [-1.8 ; 0] [-1.8 ; 0.1] [-1.8 ; 0.2] [-1.8 ; 0.3] [-1.8 ; 0.4] [-1.8 ; 0.5] [-1.8 ; 0.6] [-1.8 ; 0.7] [-1.8 ; 0.8] [-1.8 ; 0.9] [-1.8 ; 1] [-1.8 ; 1.1] [-1.8 ; 1.2] [-1.8 ; 1.3] [-1.8 ; 1.4] [-1.8 ; 1.5] [-1.8 ; 1.6] [-1.8 ; 1.7] [-1.8 ; 1.8] [-1.8 ; 1.9] [-1.8 ; 2] [-1.8 ; 2.1] [-1.8 ; 2.2] [-1.8 ; 2.3] [-1.8 ; 2.4] [-1.8 ; 2.5] [-1.8 ; 2.6] [-1.8 ; 2.7] [-1.8 ; 2.8] [-1.8 ; 2.9] [-1.8 ; 3] [-1.7 ; 0] [-1.7 ; 0.1] [-1.7 ; 0.2] [-1.7 ; 0.3] [-1.7 ; 0.4] [-1.7 ; 0.5] [-1.7 ; 0.6] [-1.7 ; 0.7] [-1.7 ; 0.8] [-1.7 ; 0.9] [-1.7 ; 1] [-1.7 ; 1.1] [-1.7 ; 1.2] [-1.7 ; 1.3] [-1.7 ; 1.4] [-1.7 ; 1.5] [-1.7 ; 1.6] [-1.7 ; 1.7] [-1.7 ; 1.8] [-1.7 ; 1.9] [-1.7 ; 2] [-1.7 ; 2.1] [-1.7 ; 2.2] [-1.7 ; 2.3] [-1.7 ; 2.4] [-1.7 ; 2.5] [-1.7 ; 2.6] [-1.7 ; 2.7] [-1.7 ; 2.8] [-1.7 ; 2.9] [-1.7 ; 3] [-1.6 ; 0] [-1.6 ; 0.1] [-1.6 ; 0.2] [-1.6 ; 0.3] [-1.6 ; 0.4] [-1.6 ; 0.5] [-1.6 ; 0.6] [-1.6 ; 0.7] [-1.6 ; 0.8] [-1.6 ; 0.9] [-1.6 ; 1] [-1.6 ; 1.1] [-1.6 ; 1.2] [-1.6 ; 1.3] [-1.6 ; 1.4] [-1.6 ; 1.5] [-1.6 ; 1.6] [-1.6 ; 1.7] [-1.6 ; 1.8] [-1.6 ; 1.9] [-1.6 ; 2] [-1.6 ; 2.1] [-1.6 ; 2.2] [-1.6 ; 2.3] [-1.6 ; 2.4] [-1.6 ; 2.5] [-1.6 ; 2.6] [-1.6 ; 2.7] [-1.6 ; 2.8] [-1.6 ; 2.9] [-1.6 ; 3] [-1.5 ; 0] [-1.5 ; 0.1] [-1.5 ; 0.2] [-1.5 ; 0.3] [-1.5 ; 0.4] [-1.5 ; 0.5] [-1.5 ; 0.6] [-1.5 ; 0.7] [-1.5 ; 0.8] [-1.5 ; 0.9] [-1.5 ; 1] [-1.5 ; 1.1] [-1.5 ; 1.2] [-1.5 ; 1.3] [-1.5 ; 1.4] [-1.5 ; 1.5] [-1.5 ; 1.6] [-1.5 ; 1.7] [-1.5 ; 1.8] [-1.5 ; 1.9] [-1.5 ; 2] [-1.5 ; 2.1] [-1.5 ; 2.2] [-1.5 ; 2.3] [-1.5 ; 2.4] [-1.5 ; 2.5] [-1.5 ; 2.6] [-1.5 ; 2.7] [-1.5 ; 2.8] [-1.5 ; 2.9] [-1.5 ; 3] [-1.4 ; 0] [-1.4 ; 0.1] [-1.4 ; 0.2] [-1.4 ; 0.3] [-1.4 ; 0.4] [-1.4 ; 0.5] [-1.4 ; 0.6] [-1.4 ; 0.7] [-1.4 ; 0.8] [-1.4 ; 0.9] [-1.4 ; 1] [-1.4 ; 1.1] [-1.4 ; 1.2] [-1.4 ; 1.3] [-1.4 ; 1.4] [-1.4 ; 1.5] [-1.4 ; 1.6] [-1.4 ; 1.7] [-1.4 ; 1.8] [-1.4 ; 1.9] [-1.4 ; 2] [-1.4 ; 2.1] [-1.4 ; 2.2] [-1.4 ; 2.3] [-1.4 ; 2.4] [-1.4 ; 2.5] [-1.4 ; 2.6] [-1.4 ; 2.7] [-1.4 ; 2.8] [-1.4 ; 2.9] [-1.4 ; 3] [-1.3 ; 0] [-1.3 ; 0.1] [-1.3 ; 0.2] [-1.3 ; 0.3] [-1.3 ; 0.4] [-1.3 ; 0.5] [-1.3 ; 0.6] [-1.3 ; 0.7] [-1.3 ; 0.8] [-1.3 ; 0.9] [-1.3 ; 1] [-1.3 ; 1.1] [-1.3 ; 1.2] [-1.3 ; 1.3] [-1.3 ; 1.4] [-1.3 ; 1.5] [-1.3 ; 1.6] [-1.3 ; 1.7] [-1.3 ; 1.8] [-1.3 ; 1.9] [-1.3 ; 2] [-1.3 ; 2.1] [-1.3 ; 2.2] [-1.3 ; 2.3] [-1.3 ; 2.4] [-1.3 ; 2.5] [-1.3 ; 2.6] [-1.3 ; 2.7] [-1.3 ; 2.8] [-1.3 ; 2.9] [-1.3 ; 3] [-1.2 ; 0] [-1.2 ; 0.1] [-1.2 ; 0.2] [-1.2 ; 0.3] [-1.2 ; 0.4] [-1.2 ; 0.5] [-1.2 ; 0.6] [-1.2 ; 0.7] [-1.2 ; 0.8] [-1.2 ; 0.9] [-1.2 ; 1] [-1.2 ; 1.1] [-1.2 ; 1.2] [-1.2 ; 1.3] [-1.2 ; 1.4] [-1.2 ; 1.5] [-1.2 ; 1.6] [-1.2 ; 1.7] [-1.2 ; 1.8] [-1.2 ; 1.9] [-1.2 ; 2] [-1.2 ; 2.1] [-1.2 ; 2.2] [-1.2 ; 2.3] [-1.2 ; 2.4] [-1.2 ; 2.5] [-1.2 ; 2.6] [-1.2 ; 2.7] [-1.2 ; 2.8] [-1.2 ; 2.9] [-1.2 ; 3] [-1.1 ; 0] [-1.1 ; 0.1] [-1.1 ; 0.2] [-1.1 ; 0.3] [-1.1 ; 0.4] [-1.1 ; 0.5] [-1.1 ; 0.6] [-1.1 ; 0.7] [-1.1 ; 0.8] [-1.1 ; 0.9] [-1.1 ; 1] [-1.1 ; 1.1] [-1.1 ; 1.2] [-1.1 ; 1.3] [-1.1 ; 1.4] [-1.1 ; 1.5] [-1.1 ; 1.6] [-1.1 ; 1.7] [-1.1 ; 1.8] [-1.1 ; 1.9] [-1.1 ; 2] [-1.1 ; 2.1] [-1.1 ; 2.2] [-1.1 ; 2.3] [-1.1 ; 2.4] [-1.1 ; 2.5] [-1.1 ; 2.6] [-1.1 ; 2.7] [-1.1 ; 2.8] [-1.1 ; 2.9] [-1.1 ; 3] [-1 ; 0] [-1 ; 0.1] [-1 ; 0.2] [-1 ; 0.3] [-1 ; 0.4] [-1 ; 0.5] [-1 ; 0.6] [-1 ; 0.7] [-1 ; 0.8] [-1 ; 0.9] [-1 ; 1] [-1 ; 1.1] [-1 ; 1.2] [-1 ; 1.3] [-1 ; 1.4] [-1 ; 1.5] [-1 ; 1.6] [-1 ; 1.7] [-1 ; 1.8] [-1 ; 1.9] [-1 ; 2] [-1 ; 2.1] [-1 ; 2.2] [-1 ; 2.3] [-1 ; 2.4] [-1 ; 2.5] [-1 ; 2.6] [-1 ; 2.7] [-1 ; 2.8] [-1 ; 2.9] [-1 ; 3] [-0.9 ; 0] [-0.9 ; 0.1] [-0.9 ; 0.2] [-0.9 ; 0.3] [-0.9 ; 0.4] [-0.9 ; 0.5] [-0.9 ; 0.6] [-0.9 ; 0.7] [-0.9 ; 0.8] [-0.9 ; 0.9] [-0.9 ; 1] [-0.9 ; 1.1] [-0.9 ; 1.2] [-0.9 ; 1.3] [-0.9 ; 1.4] [-0.9 ; 1.5] [-0.9 ; 1.6] [-0.9 ; 1.7] [-0.9 ; 1.8] [-0.9 ; 1.9] [-0.9 ; 2] [-0.9 ; 2.1] [-0.9 ; 2.2] [-0.9 ; 2.3] [-0.9 ; 2.4] [-0.9 ; 2.5] [-0.9 ; 2.6] [-0.9 ; 2.7] [-0.9 ; 2.8] [-0.9 ; 2.9] [-0.9 ; 3] [-0.8 ; 0] [-0.8 ; 0.1] [-0.8 ; 0.2] [-0.8 ; 0.3] [-0.8 ; 0.4] [-0.8 ; 0.5] [-0.8 ; 0.6] [-0.8 ; 0.7] [-0.8 ; 0.8] [-0.8 ; 0.9] [-0.8 ; 1] [-0.8 ; 1.1] [-0.8 ; 1.2] [-0.8 ; 1.3] [-0.8 ; 1.4] [-0.8 ; 1.5] [-0.8 ; 1.6] [-0.8 ; 1.7] [-0.8 ; 1.8] [-0.8 ; 1.9] [-0.8 ; 2] [-0.8 ; 2.1] [-0.8 ; 2.2] [-0.8 ; 2.3] [-0.8 ; 2.4] [-0.8 ; 2.5] [-0.8 ; 2.6] [-0.8 ; 2.7] [-0.8 ; 2.8] [-0.8 ; 2.9] [-0.8 ; 3] [-0.7 ; 0] [-0.7 ; 0.1] [-0.7 ; 0.2] [-0.7 ; 0.3] [-0.7 ; 0.4] [-0.7 ; 0.5] [-0.7 ; 0.6] [-0.7 ; 0.7] [-0.7 ; 0.8] [-0.7 ; 0.9] [-0.7 ; 1] [-0.7 ; 1.1] [-0.7 ; 1.2] [-0.7 ; 1.3] [-0.7 ; 1.4] [-0.7 ; 1.5] [-0.7 ; 1.6] [-0.7 ; 1.7] [-0.7 ; 1.8] [-0.7 ; 1.9] [-0.7 ; 2] [-0.7 ; 2.1] [-0.7 ; 2.2] [-0.7 ; 2.3] [-0.7 ; 2.4] [-0.7 ; 2.5] [-0.7 ; 2.6] [-0.7 ; 2.7] [-0.7 ; 2.8] [-0.7 ; 2.9] [-0.7 ; 3] [-0.6 ; 0] [-0.6 ; 0.1] [-0.6 ; 0.2] [-0.6 ; 0.3] [-0.6 ; 0.4] [-0.6 ; 0.5] [-0.6 ; 0.6] [-0.6 ; 0.7] [-0.6 ; 0.8] [-0.6 ; 0.9] [-0.6 ; 1] [-0.6 ; 1.1] [-0.6 ; 1.2] [-0.6 ; 1.3] [-0.6 ; 1.4] [-0.6 ; 1.5] [-0.6 ; 1.6] [-0.6 ; 1.7] [-0.6 ; 1.8] [-0.6 ; 1.9] [-0.6 ; 2] [-0.6 ; 2.1] [-0.6 ; 2.2] [-0.6 ; 2.3] [-0.6 ; 2.4] [-0.6 ; 2.5] [-0.6 ; 2.6] [-0.6 ; 2.7] [-0.6 ; 2.8] [-0.6 ; 2.9] [-0.6 ; 3] [-0.5 ; 0] [-0.5 ; 0.1] [-0.5 ; 0.2] [-0.5 ; 0.3] [-0.5 ; 0.4] [-0.5 ; 0.5] [-0.5 ; 0.6] [-0.5 ; 0.7] [-0.5 ; 0.8] [-0.5 ; 0.9] [-0.5 ; 1] [-0.5 ; 1.1] [-0.5 ; 1.2] [-0.5 ; 1.3] [-0.5 ; 1.4] [-0.5 ; 1.5] [-0.5 ; 1.6] [-0.5 ; 1.7] [-0.5 ; 1.8] [-0.5 ; 1.9] [-0.5 ; 2] [-0.5 ; 2.1] [-0.5 ; 2.2] [-0.5 ; 2.3] [-0.5 ; 2.4] [-0.5 ; 2.5] [-0.5 ; 2.6] [-0.5 ; 2.7] [-0.5 ; 2.8] [-0.5 ; 2.9] [-0.5 ; 3] [-0.4 ; 0] [-0.4 ; 0.1] [-0.4 ; 0.2] [-0.4 ; 0.3] [-0.4 ; 0.4] [-0.4 ; 0.5] [-0.4 ; 0.6] [-0.4 ; 0.7] [-0.4 ; 0.8] [-0.4 ; 0.9] [-0.4 ; 1] [-0.4 ; 1.1] [-0.4 ; 1.2] [-0.4 ; 1.3] [-0.4 ; 1.4] [-0.4 ; 1.5] [-0.4 ; 1.6] [-0.4 ; 1.7] [-0.4 ; 1.8] [-0.4 ; 1.9] [-0.4 ; 2] [-0.4 ; 2.1] [-0.4 ; 2.2] [-0.4 ; 2.3] [-0.4 ; 2.4] [-0.4 ; 2.5] [-0.4 ; 2.6] [-0.4 ; 2.7] [-0.4 ; 2.8] [-0.4 ; 2.9] [-0.4 ; 3] [-0.3 ; 0] [-0.3 ; 0.1] [-0.3 ; 0.2] [-0.3 ; 0.3] [-0.3 ; 0.4] [-0.3 ; 0.5] [-0.3 ; 0.6] [-0.3 ; 0.7] [-0.3 ; 0.8] [-0.3 ; 0.9] [-0.3 ; 1] [-0.3 ; 1.1] [-0.3 ; 1.2] [-0.3 ; 1.3] [-0.3 ; 1.4] [-0.3 ; 1.5] [-0.3 ; 1.6] [-0.3 ; 1.7] [-0.3 ; 1.8] [-0.3 ; 1.9] [-0.3 ; 2] [-0.3 ; 2.1] [-0.3 ; 2.2] [-0.3 ; 2.3] [-0.3 ; 2.4] [-0.3 ; 2.5] [-0.3 ; 2.6] [-0.3 ; 2.7] [-0.3 ; 2.8] [-0.3 ; 2.9] [-0.3 ; 3] [-0.2 ; 0] [-0.2 ; 0.1] [-0.2 ; 0.2] [-0.2 ; 0.3] [-0.2 ; 0.4] [-0.2 ; 0.5] [-0.2 ; 0.6] [-0.2 ; 0.7] [-0.2 ; 0.8] [-0.2 ; 0.9] [-0.2 ; 1] [-0.2 ; 1.1] [-0.2 ; 1.2] [-0.2 ; 1.3] [-0.2 ; 1.4] [-0.2 ; 1.5] [-0.2 ; 1.6] [-0.2 ; 1.7] [-0.2 ; 1.8] [-0.2 ; 1.9] [-0.2 ; 2] [-0.2 ; 2.1] [-0.2 ; 2.2] [-0.2 ; 2.3] [-0.2 ; 2.4] [-0.2 ; 2.5] [-0.2 ; 2.6] [-0.2 ; 2.7] [-0.2 ; 2.8] [-0.2 ; 2.9] [-0.2 ; 3] [-0.1 ; 0] [-0.1 ; 0.1] [-0.1 ; 0.2] [-0.1 ; 0.3] [-0.1 ; 0.4] [-0.1 ; 0.5] [-0.1 ; 0.6] [-0.1 ; 0.7] [-0.1 ; 0.8] [-0.1 ; 0.9] [-0.1 ; 1] [-0.1 ; 1.1] [-0.1 ; 1.2] [-0.1 ; 1.3] [-0.1 ; 1.4] [-0.1 ; 1.5] [-0.1 ; 1.6] [-0.1 ; 1.7] [-0.1 ; 1.8] [-0.1 ; 1.9] [-0.1 ; 2] [-0.1 ; 2.1] [-0.1 ; 2.2] [-0.1 ; 2.3] [-0.1 ; 2.4] [-0.1 ; 2.5] [-0.1 ; 2.6] [-0.1 ; 2.7] [-0.1 ; 2.8] [-0.1 ; 2.9] [-0.1 ; 3] [0 ; 0] [0 ; 0.1] [0 ; 0.2] [0 ; 0.3] [0 ; 0.4] [0 ; 0.5] [0 ; 0.6] [0 ; 0.7] [0 ; 0.8] [0 ; 0.9] [0 ; 1] [0 ; 1.1] [0 ; 1.2] [0 ; 1.3] [0 ; 1.4] [0 ; 1.5] [0 ; 1.6] [0 ; 1.7] [0 ; 1.8] [0 ; 1.9] [0 ; 2] [0 ; 2.1] [0 ; 2.2] [0 ; 2.3] [0 ; 2.4] [0 ; 2.5] [0 ; 2.6] [0 ; 2.7] [0 ; 2.8] [0 ; 2.9] [0 ; 3] [0.1 ; 0] [0.1 ; 0.1] [0.1 ; 0.2] [0.1 ; 0.3] [0.1 ; 0.4] [0.1 ; 0.5] [0.1 ; 0.6] [0.1 ; 0.7] [0.1 ; 0.8] [0.1 ; 0.9] [0.1 ; 1] [0.1 ; 1.1] [0.1 ; 1.2] [0.1 ; 1.3] [0.1 ; 1.4] [0.1 ; 1.5] [0.1 ; 1.6] [0.1 ; 1.7] [0.1 ; 1.8] [0.1 ; 1.9] [0.1 ; 2] [0.1 ; 2.1] [0.1 ; 2.2] [0.1 ; 2.3] [0.1 ; 2.4] [0.1 ; 2.5] [0.1 ; 2.6] [0.1 ; 2.7] [0.1 ; 2.8] [0.1 ; 2.9] [0.1 ; 3] [0.2 ; 0] [0.2 ; 0.1] [0.2 ; 0.2] [0.2 ; 0.3] [0.2 ; 0.4] [0.2 ; 0.5] [0.2 ; 0.6] [0.2 ; 0.7] [0.2 ; 0.8] [0.2 ; 0.9] [0.2 ; 1] [0.2 ; 1.1] [0.2 ; 1.2] [0.2 ; 1.3] [0.2 ; 1.4] [0.2 ; 1.5] [0.2 ; 1.6] [0.2 ; 1.7] [0.2 ; 1.8] [0.2 ; 1.9] [0.2 ; 2] [0.2 ; 2.1] [0.2 ; 2.2] [0.2 ; 2.3] [0.2 ; 2.4] [0.2 ; 2.5] [0.2 ; 2.6] [0.2 ; 2.7] [0.2 ; 2.8] [0.2 ; 2.9] [0.2 ; 3] [0.3 ; 0] [0.3 ; 0.1] [0.3 ; 0.2] [0.3 ; 0.3] [0.3 ; 0.4] [0.3 ; 0.5] [0.3 ; 0.6] [0.3 ; 0.7] [0.3 ; 0.8] [0.3 ; 0.9] [0.3 ; 1] [0.3 ; 1.1] [0.3 ; 1.2] [0.3 ; 1.3] [0.3 ; 1.4] [0.3 ; 1.5] [0.3 ; 1.6] [0.3 ; 1.7] [0.3 ; 1.8] [0.3 ; 1.9] [0.3 ; 2] [0.3 ; 2.1] [0.3 ; 2.2] [0.3 ; 2.3] [0.3 ; 2.4] [0.3 ; 2.5] [0.3 ; 2.6] [0.3 ; 2.7] [0.3 ; 2.8] [0.3 ; 2.9] [0.3 ; 3] [0.4 ; 0] [0.4 ; 0.1] [0.4 ; 0.2] [0.4 ; 0.3] [0.4 ; 0.4] [0.4 ; 0.5] [0.4 ; 0.6] [0.4 ; 0.7] [0.4 ; 0.8] [0.4 ; 0.9] [0.4 ; 1] [0.4 ; 1.1] [0.4 ; 1.2] [0.4 ; 1.3] [0.4 ; 1.4] [0.4 ; 1.5] [0.4 ; 1.6] [0.4 ; 1.7] [0.4 ; 1.8] [0.4 ; 1.9] [0.4 ; 2] [0.4 ; 2.1] [0.4 ; 2.2] [0.4 ; 2.3] [0.4 ; 2.4] [0.4 ; 2.5] [0.4 ; 2.6] [0.4 ; 2.7] [0.4 ; 2.8] [0.4 ; 2.9] [0.4 ; 3] [0.5 ; 0] [0.5 ; 0.1] [0.5 ; 0.2] [0.5 ; 0.3] [0.5 ; 0.4] [0.5 ; 0.5] [0.5 ; 0.6] [0.5 ; 0.7] [0.5 ; 0.8] [0.5 ; 0.9] [0.5 ; 1] [0.5 ; 1.1] [0.5 ; 1.2] [0.5 ; 1.3] [0.5 ; 1.4] [0.5 ; 1.5] [0.5 ; 1.6] [0.5 ; 1.7] [0.5 ; 1.8] [0.5 ; 1.9] [0.5 ; 2] [0.5 ; 2.1] [0.5 ; 2.2] [0.5 ; 2.3] [0.5 ; 2.4] [0.5 ; 2.5] [0.5 ; 2.6] [0.5 ; 2.7] [0.5 ; 2.8] [0.5 ; 2.9] [0.5 ; 3]];  
T=[0 0 0 0 0 0 0 0 0 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0 0 0 0 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 0.0003 0.0003 0.0003 0.0003 0.0003 0.0003 0.0003 0.0003 0.0003 0.0003 0 0 0.0001 0.0001 0.0001 0.0002 0.0002 0.0002 0.0002 0.0003 0.0003 0.0003 0.0003 0.0004 0.0004 0.0004 0.0004 0.0005 0.0005 0.0005 0.0005 0.0006 0.0006 0.0006 0.0006 0.0007 0.0007 0.0007 0.0007 0.0007 0.0008 0 0.0001 0.0001 0.0002 0.0003 0.0004 0.0004 0.0005 0.0005 0.0006 0.0007 0.0007 0.0008 0.0008 0.0009 0.001 0.001 0.0011 0.0011 0.0012 0.0012 0.0013 0.0014 0.0014 0.0015 0.0015 0.0016 0.0016 0.0017 0.0017 0.0018 0 0.0002 0.0003 0.0005 0.0006 0.0008 0.0009 0.0011 0.0012 0.0014 0.0015 0.0017 0.0018 0.0019 0.0021 0.0022 0.0023 0.0025 0.0026 0.0027 0.0028 0.003 0.0031 0.0032 0.0033 0.0035 0.0036 0.0037 0.0038 0.0039 0.004 0 0.0004 0.0008 0.0011 0.0015 0.0018 0.0022 0.0025 0.0028 0.0032 0.0035 0.0038 0.0041 0.0044 0.0048 0.0051 0.0054 0.0057 0.006 0.0063 0.0065 0.0068 0.0071 0.0074 0.0077 0.0079 0.0082 0.0085 0.0087 0.009 0.0093 0 0.0009 0.0017 0.0025 0.0034 0.0042 0.005 0.0057 0.0065 0.0073 0.008 0.0088 0.0095 0.0102 0.0109 0.0116 0.0123 0.013 0.0137 0.0144 0.015 0.0157 0.0163 0.017 0.0176 0.0182 0.0188 0.0195 0.0201 0.0207 0.0213 0 0.002 0.0039 0.0058 0.0077 0.0095 0.0114 0.0132 0.0149 0.0167 0.0184 0.0201 0.0218 0.0234 0.0251 0.0267 0.0283 0.0299 0.0314 0.033 0.0345 0.036 0.0375 0.039 0.0404 0.0419 0.0433 0.0447 0.0461 0.0475 0.0488 0 0.0045 0.009 0.0133 0.0176 0.0219 0.026 0.0302 0.0342 0.0382 0.0422 0.0461 0.05 0.0538 0.0575 0.0613 0.0649 0.0685 0.0721 0.0757 0.0792 0.0826 0.086 0.0894 0.0928 0.0961 0.0994 0.1026 0.1058 0.109 0.1121 0 0.0103 0.0205 0.0305 0.0403 0.05 0.0596 0.069 0.0783 0.0875 0.0966 0.1055 0.1144 0.1231 0.1317 0.1402 0.1486 0.1569 0.1651 0.1732 0.1812 0.1891 0.197 0.2047 0.2124 0.2199 0.2274 0.2348 0.2422 0.2494 0.2566 0 0.0235 0.0466 0.0693 0.0917 0.1138 0.1355 0.157 0.1782 0.1991 0.2197 0.2401 0.2602 0.28 0.2996 0.3189 0.3381 0.3569 0.3756 0.394 0.4123 0.4303 0.4481 0.4657 0.4831 0.5004 0.5174 0.5343 0.551 0.5675 0.5838 0 0.0526 0.1044 0.1554 0.2056 0.2552 0.304 0.3521 0.3996 0.4465 0.4928 0.5384 0.5835 0.628 0.672 0.7154 0.7583 0.8006 0.8425 0.8839 0.9248 0.9652 1.0052 1.0447 1.0837 1.1244 1.1606 1.1984 1.2359 1.2729 1.3095 0 0.1145 0.2272 0.3381 0.4474 0.5551 0.6613 0.7661 0.8694 0.9714 1.072 1.1713 1.2694 1.3662 1.4618 1.5563 1.6496 1.7417 1.8328 1.9228 2.0117 2.0997 2.1866 2.2726 2.3576 2.4417 2.5248 2.6071 2.6885 2.769 2.8487 0 0.2344 0.465 0.6918 0.9152 1.1355 1.3526 1.5668 1.778 1.9865 2.1922 2.3953 2.5957 2.7936 2.9891 3.1821 3.3728 3.5612 3.7474 3.9314 4.1132 4.293 4.4707 4.6464 4.8202 4.9921 5.1621 5.3303 5.4967 5.6613 5.8243 0 0.4351 0.8609 1.2779 1.6876 2.091 2.4886 2.8808 3.2676 3.6493 4.0259 4.3977 4.7647 5.1271 5.485 5.8384 6.1876 6.5325 6.8734 7.2103 7.5432 7.8723 8.1977 8.5194 8.8376 9.1523 9.4636 9.7715 10.0762 10.3776 10.6759 0 1.1927 2.1763 2.9713 3.6672 4.3183 4.9476 5.5638 6.1701 6.7678 7.3574 7.9394 8.5139 9.0811 9.6412 10.1945 10.741 11.2809 11.8144 12.3417 12.8628 13.3779 13.8872 14.3908 14.8889 15.3814 15.8686 16.3506 16.8274 17.2993 17.7662 0 5.1477 8.6615 10.7074 12.0102 13.0102 13.8925 14.7261 15.5357 16.3301 17.1124 17.8841 18.6458 19.3977 20.1403 20.8737 21.5981 22.3139 23.0211 23.7201 24.4109 25.0938 25.769 26.4366 27.0968 27.7497 28.3956 29.0345 29.6666 30.2921 30.9111 0 12.0627 19.9146 23.9851 26.1497 27.5473 28.657 29.6566 30.6095 31.5383 32.4508 33.3501 34.2375 35.1134 35.9784 36.8327 37.6766 38.5104 39.3342 40.1484 40.9531 41.7486 42.535 43.3127 44.0817 44.8423 45.5946 46.3389 47.0752 47.8038 48.5249 0 20.7322 33.985 40.522 43.6789 45.4813 46.781 47.8942 48.9333 49.9382 50.9227 51.8919 52.8479 53.7916 54.7233 55.6435 56.5526 57.4507 58.3381 59.2151 60.0819 60.9388 61.7859 62.6236 63.4519 64.2712 65.0816 65.8833 66.6765 67.4613 68.238 0 30.0915 49.1578 58.3248 62.5125 64.7091 66.1705 67.3629 68.4523 69.4969 70.5173 71.5207 72.5101 73.4866 74.4507 75.4029 76.3434 77.2727 78.1909 79.0983 79.9952 80.8819 81.7584 82.6251 83.4822 84.33 85.1685 85.998 86.8187 87.6308 88.4344 0 39.2571 64.0091 75.7376 80.9178 83.4821 85.0833 86.3349 87.4552 88.5207 89.5585 90.5779 91.5826 92.5741 93.533 94.5198 95.4748 96.4183 97.3505 98.2719 99.1825 100.0827 100.9727 101.8527 102.7229 103.5836 104.4349 105.2771 106.1104 106.9349 107.7509 0 47.5742 77.4826 91.5298 97.6036 100.4942 102.2148 103.5127 104.6537 105.7309 106.7772 107.804 108.8157 109.8139 110.7993 111.7726 112.734 113.6838 114.6223 115.5498 116.4665 117.3728 118.2687 119.1546 120.0307 120.8971 121.7542 122.602 123.4409 124.2709 125.0923 0 54.6683 88.9736 104.9963 111.8296 114.9956 116.815 118.1494 119.3051 120.3895 121.4401 122.4705 123.4852 124.4864 125.4748 126.4509 127.4151 128.3676 129.3089 130.2391 131.1585 132.0674 132.9659 133.8544 134.7331 135.602 136.4616 137.3119 138.1532 138.9857 139.8095 0 60.4719 98.3737 116.0117 123.4652 126.8552 128.7544 130.1174 131.284 132.3729 133.4261 134.4581 135.4743 136.4768 137.4664 138.4438 139.4092 140.363 141.3055 142.2368 143.1574 144.0674 144.9671 145.8576 146.7365 147.6066 148.4672 149.3186 150.161 150.9945 151.8194 0 64.7235 105.2601 124.0811 131.9885 135.5423 137.4994 138.8831 140.0571 141.1491 142.2037 143.2365 144.2534 145.2565 146.2467 147.2246 148.1905 149.1448 150.0878 151.0197 151.9408 152.8513 153.7515 154.6416 155.5219 156.3924 157.2536 158.1054 158.9483 159.7823 160.6076 0 65.5112 106.5359 125.5762 133.5679 137.1521 139.1201 140.5078 141.6834 142.7761 143.831 144.8642 145.8813 146.8846 147.8751 148.8532 149.8194 150.774 151.7172 152.6493 153.5706 154.4813 155.3818 156.2721 157.1525 158.0233 158.8846 159.7367 160.5797 161.4139 162.2394];
   
net.performFcn='mse';           %funcion de actuacion (Mse) --> aprox. de funciones

%entrenamos la red
net=newff(minmax(P),[1 1 1 1 1 1 ],{'tansig' 'purelin' 'purelin' 'purelin' 'tansig' 'purelin'},'trainlm');
net.trainParam.goal=0.000001;
net.trainParam.epochs=1000;
net.trainParam.show=100;
net=train(net,P,T);

net.b{2}=1;                     %biases capa 2 y 4 valen 1 (ver red)
net.b{4}=1;

net.LW{2,1}=1;                  %pesos inicializados a 1 (ver red)
net.LW{4,3}=1;
net.LW{6,4}=1;                  %al simular me dice q este peso debe ser una matriz vacia: POR QUE?????
net.LW{6,5}=1;

Y=sim(net,P);

correlacion=corrcoef(Y,T)
pause;

[m,b,r]=postreg(Y,T)
pause;
figure;

%representacion grafica de los datos
P1=[-2 -1.9 -1.8 -1.7 -1.6 -1.5 -1.4 -1.3 -1.2 -1.1 -1 -0.9 -0.8 -0.7 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5];
P2=[0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 3];

Datos=reshape(T,length(P2),length(P1));
Sim=reshape(Y,length(P2),length(P1));

mesh(P1,P2,Datos);              %datos teoricos
figure;

mesh(P1,P2,Sim);                %datos tras la simulacion


%obtencion de los pesos y bias deseados (POR QUE SALEN ERRORES EN ALGUNOS????)
Q1=net.b{1,1}                    %-Q1