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

Hola. Kiero fijar unos determinados pesos y bias de una red neuronal a 1. ¿Cómo lo hago? He probado con varias cosas pero no sale. Si alguien sabe algo, responda por akí o a mi correo (jmanguasp@hotmail.com). Un saludo y gracias!

Ya esta solucionado en parte. Keria representar:

P=[[-2 0] [-2 0.1] [-2 0.2]...[-2 3] [-1.9 0] [-1.9 0.1]...........[0.5 3]]

yotro vector T con el mismo nro de elemtos de P. Pues se hace usando:

plot3(P(1,:),P(2,:),T);
grid on;

Pero ahora kiero poner la gráfica (los resultados, no los ejes) en forma de cuadrícula, en luga de líneas. ¿Sabeis como hacerlo??

Os mand el fichero para q veais las líneas q salen y lo tengais más claro!!

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] [-0.9 ; 1.7] [-0.9 ; 1.8] [-0.9 ; 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 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 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 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 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 0 0 0 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 0.0003 0.0003 0.0003 0.0003 0.0003 0.0003 0.0003 0.0004 0.0004 0.0004 0.0004 0.0004 0.0004 0.0004 0.0005 0.0005 0 0 0.0001 0.0001 0.0002 0.0002 0.0003 0.0003 0.0003 0.0004 0.0004 0.0004 0.0005 0.0005 0.0006 0.0006 0.0006 0.0007 0.0007 0.0007 0.0008 0.0008 0.0008 0.0009 0.0009 0.0009 0.001 0.001 0.001 0.001 0.0011 0 0.0001 0.0002 0.0003 0.0004 0.0005 0.0006 0.0007 0.0008 0.0008 0.0009 0.001 0.0011 0.0012 0.0013 0.0014 0.0014 0.0015 0.0016 0.0017 0.0017 0.0018 0.0019 0.002 0.002 0.0021 0.0022 0.0023 0.0023 0.0024 0.0025 0 0.0002 0.0005 0.0007 0.0009 0.0011 0.0013 0.0015 0.0017 0.0019 0.0021 0.0023 0.0025 0.0027 0.0029 0.0031 0.0033 0.0035 0.0036 0.0038 0.004 0.0042 0.0044 0.0045 0.0047 0.0049 0.005 0.0052 0.0053 0.0055 0.0057 0 0.0005 0.001 0.0016 0.0021 0.0025 0.003 0.0035 0.004 0.0044 0.0049 0.0054 0.0058 0.0063 0.0067 0.0071 0.0075 0.008 0.0084 0.0088 0.0092 0.0096 0.01 0.0104 0.0108 0.0112 0.0115 0.0119 0.0123 0.0127 0.013 0 0.0012 0.0024 0.0036 0.0047 0.0058 0.0069 0.008 0.0091 0.0102 0.0113 0.0123 0.0133 0.0143 0.0153 0.0163 0.0173 0.0183 0.0192 0.0202 0.0211 0.022 0.0229 0.0238 0.0247 0.0256 0.0265 0.0274 0.0282 0.0291 0.0299 0 0.0028 0.0055 0.0081 0.0108 0.0133 0.0159 0.0184 0.0209 0.0233 0.0258 0.0281 0.0305 0.0328 0.0351 0.0374 0.0396 0.0418 0.044 0.0462 0.0483 0.0504 0.0525 0.0546 0.0566 0.0587 0.0606 0.0626 0.0646 0.0665 0.0684 0 0.0063 0.0124 0.0185 0.0245 0.0303 0.0361 0.0419 0.0475 0.0531 0.0586 0.064 0.0694 0.0747 0.0799 0.085 0.0901 0.0952 0.1002 0.1051 0.1099 0.1147 0.1195 0.1242 0.1288 0.1334 0.138 0.1425 0.1469 0.1513 0.1557 0 0.014 0.0278 0.0414 0.0548 0.068 0.0811 0.0939 0.1066 0.1191 0.1314 0.1436 0.1556 0.1675 0.1792 0.1908 0.2022 0.2135 0.2247 0.2357 0.2466 0.2574 0.268 0.2786 0.289 0.2993 0.3095 0.3196 0.3296 0.3394 0.3492 0 0.0305 0.0606 0.0902 0.1193 0.148 0.1763 0.2043 0.2318 0.259 0.2859 0.3124 0.3385 0.3643 0.3898 0.415 0.4399 0.4645 0.4887 0.5127 0.5365 0.5599 0.5831 0.606 0.6287 0.6511 0.6733 0.6952 0.7169 0.7384 0.7597 0 0.0625 0.124 0.1845 0.2441 0.3028 0.3607 0.4178 0.4741 0.5297 0.5846 0.6387 0.6922 0.745 0.7971 0.8486 0.8994 0.9497 0.9993 1.0484 1.0969 1.1448 1.1922 1.2391 1.2854 1.3312 1.3766 1.4214 1.4658 1.5097 1.5531 0 0.116 0.2296 0.3408 0.45 0.5576 0.6636 0.7682 0.8714 0.9731 1.0736 1.1727 1.2706 1.3672 1.4627 1.5569 1.65 1.742 1.8329 1.9927 2.0115 2.0993 2.1861 2.2719 2.3567 2.4406 2.5236 2.6057 2.687 2.7674 2.8469 0 0.3181 0.5803 0.7924 0.9779 1.1515 1.3194 1.4837 1.6454 1.8047 1.962 2.1172 2.2704 2.4216 2.571 2.7185 2.8643 3.0082 3.1505 3.2911 3.4301 3.5674 3.7033 3.8376 3.9704 4.1017 4.2316 4.3602 4.4873 4.6131 4.7377 0 1.3721 2.3097 2.8553 3.2027 3.4694 3.7047 3.927 4.1429 4.3547 4.5633 4.7691 4.9722 5.1727 5.3707 5.5663 5.7595 5.9504 6.139 6.3254 6.5096 6.6917 6.8717 7.0498 7.2258 7.3999 7.5721 7.7425 7.9111 8.0779 8.243 0 3.2167 5.3106 6.396 6.9732 7.3459 7.6419 7.9084 8.1625 8.4102 8.6536 8.8934 9.13 9.3636 9.5942 9.8221 10.0471 10.2694 10.4891 10.7062 10.9208 11.133 11.3427 11.55 11.7551 11.9579 12.1586 12.357 12.5534 12.7477 12.94 0 5.5286 9.0627 10.8059 11.6477 12.1284 12.4749 12.7718 13.0489 13.3168 13.5794 13.8378 14.0928 14.3444 14.5929 14.8383 15.0807 15.3202 15.5568 15.7907 16.0218 16.2503 16.4762 16.6996 16.9205 17.139 17.3551 17.5689 17.7804 17.9897 18.1968 0 8.0244 13.1087 15.5533 16.67 17.2558 17.6455 17.9634 18.2539 18.5325 18.8046 19.0722 19.336 19.5964 19.8535 20.1074 20.3583 20.6061 20.8509 21.0929 21.3321 21.5685 21.8022 22.0334 22.2619 22.488 22.7116 22.9328 23.1516 23.3682 23.5825 0 10.4686 17.0691 20.1967 21.5781 22.2619 22.6889 23.0226 23.3214 23.6055 23.8823 24.1541 24.422 24.6864 24.9475 25.2053 25.4599 25.7115 25.9601 26.2058 26.4487 26.6887 26.926 27.1607 27.3928 27.6223 27.8493 28.0739 28.2961 28.516 28.7336 0 12.6865 20.662 24.4079 26.0276 26.7985 27.2573 27.6034 27.9076 28.1949 28.4739 28.7477 29.0175 29.2837 29.5465 29.806 30.0624 30.3157 30.5659 30.8133 31.0577 31.2994 31.5383 31.7746 32.0082 32.2392 32.4678 32.6939 32.9176 33.1389 33.3579 0 14.5782 23.7263 27.999 29.8212 30.6655 31.1507 31.5065 31.8147 32.1039 32.384 32.6588 32.9294 33.1964 33.4599 33.7202 33.9773 34.2314 34.4824 34.7304 34.9756 35.218 35.4576 35.6945 35.9288 36.1605 36.3898 36.6165 36.8409 37.0628 37.2825 0 16.1258 26.233 30.9365 32.9241 33.8281 34.3345 34.698 35.0091 35.2995 35.5803 35.8555 36.1265 36.3938 36.6577 36.9183 37.1758 37.4301 37.6815 37.9298 38.1753 38.418 38.6579 38.8951 39.1297 39.3618 39.5913 39.8183 40.0429 40.2652 40.4852 0 17.4697 28.4096 33.0883 35.1969 36.1446 36.6665 37.0355 37.3486 37.6398 37.921 38.1964 38.4676 38.7351 38.9991 39.2599 39.5157 39.772 40.0234 40.2719 40.5176 40.7604 41.0004 41.2378 41.4725 41.7046 41.9343 42.1615 42.3862 42.6086 42.8287 0 17.4697 28.4096 33.487 35.6181 36.5739 37.0987 37.4687 37.7822 38.0736 38.3549 38.6305 38.9017 39.1692 39.4334 39.6942 39.9518 40.2064 40.4579 40.7065 40.9522 41.195 41.4351 41.6726 41.9073 42.1395 42.3692 42.5965 42.8213 43.0437 43.2638];      

plot3(P(1,:),P(2,:),T);
grid on;

Ya no hace falta. He proado haciendo

P=[[-2 0] [-2 0.1] [-2 0.2] ... [-2 3] [-1.9 0] [-1.9 0.1] [-1.9 0.2] ........ [0.5 3]];

y poniendo en T los valores correspondientes

T=[t11 t12 t13 ... t1n t21 t22 t23 ... t2n ........... tm1 tm2 ... tmn]

Aquí os lo pongo por si os hace falta

Hola, q tal? Necesito saber si hay una función, q creo q no, en el toolbox de redes neuronales de matlab q haga y=exp(x^2). Lo he buscado y no lo he encontrao pero he visto q hay la posibilidad de crear una función de transferencia propia con 'mytf'. Así, para crear lo q necesito, tendría q dejar mytf tal cual salvo la línea en la q se expresa la relación entre 'a' y 'n' y poner ahí a=exp(n^2)??? Un saludo

Hola, tengo una red con dos entradas y una salida. Las entradas son Vgs, con rango [-2 0.5] y Vds, con rango [0 3] (ambas entradas van variando de 0.1 en 0.1). Así, tendré diferentes valores de salida para las diferentes combinaciones de entrada. Es decir, un valor de salida para el par de entrada [-2 0], otro para [-2 0.1], [-2 0.2],...,[-2 3],[-1.9 0],[-1.9 0.1],...etc. ¿cómo se pone esto usando el toolbox de redes neuronales? Gracias!

Hola q tal? Estoy tratando de realizar un estudio sobre el comportamiento de diversos transistores con redes neuronales (para simular sus comportamientos). Hago pues varias redes, y creo q tengo el mismo falo en todas. Aver si m podeis ayudar. Os explico la red mas sencilla.
Se trata de una red feedforward con dos capas y una neurona por capa. La primera neurona es 'purelin' y la segunda 'tansig', necesarias para q de el resultado deseado. Pues bien, siguiendo el tutorial a rajatabal y la ayuda, no salen los valors deseados. Me han dicho q es posible q el error pueda trenerlo en la inicializacion de los pesos, q la hago aleatoria y deberia ser fija, pero he probao cn esto ultimo y tampoco. Os dejo aqui el codigo, q es muy sencillito por si alguno sabe q puede pasarme., q es q estoy desesperao la verdad. Un saludo y muxas gracias a todos

Hola,
yo también estoy haciendo el proyecto sobre redes neuronales, aunque aplicadas al procesamiento del lenguaje natural. Sin embargo, no te puedo ayudar porque nunca he visto ninguna aplicación de redes neuronales como la que pretendes hacer. ¿Me podrías dar alguna referencia bibliográfica para ponerme al día?

Gracias.

Hace tiempo q dejé aparcao el proyecto y lo he retomao ahora. Una buena referencia bibliográfica, si aún la estás buscando, es Neural Networks de Simon Haykins.
Si sigus cn el proyecto aun, agrégame y pregunt al correo o por msn. Es más rápido.
Un saludo