How to use a trained neural network for fitting new data?

1 次查看(过去 30 天)
I've trained a neural network using a bessel function, and I've gotten a result I'm satisfied with.
Now I want to use the neural network to "smooth the curve" (get rid of the noise)
I am unable to do so, I don't know which function to use, or the correct syntaxis with the variables I have.
Paso 0
clear,clc,close all
load('reto1.mat')
Visualizar los datos
plot(t,S)
hold on
plot(t,I)
hold on
plot(t,R)
hold off
Crear la red neuronal
x = 0:100;
y = real(besselj(0,x));
Red_raza = feedforwardnet([20 10 8 5], 'trainbr');
net.trainParam.show = 1*10^-5;
net.trainParam.lr = 0.5;
net.train.Param.epochs = 1*10^25;
net.train.Param.goal = 1*10;
% net.divideParam.trainRatio = 70/100;
% net.divideParam.valRatio = 15/100;
% net.divideParam.testRatio = 15/100;
net1 = train(Red_raza,x,y);
a = sim(net1,x);
plot(x,a,'o',x,y);
Reto1 is the data I want to use my trained neural network on, which has S, I, and R as dependent variables of t.
I think I can use the neural network to remove the noise on S,I, and R independently and have appropiate curves.

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R2021a

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