MATLAB: Neural Net Fitting, NARX

narxtarget datatime series data

I have 1×15000 timeseries input data, i want to predict the next data using the Neural Net fitting toolbox/neural net timeseries. But i don't know how to define the

"target" data set?

Best Answer

Refer to the documentation of narnet. You can prepare the data using preparets.

Related Solutions

MATLAB: Data curve fitting, connecting point

Karim,

lose the for loop and just issue the plot command as shown below

clear; close all; clc;
% Specify value for Variables: 
s_TO = 1000; % take off distance in feet 
s_GTO = s_TO/1.66; % ground roll take off distance in ft 
sigma = 1; % density ratio
% enter range for max lift coefficient for Take-Off 
C_LmaxTO_begin = 1.2; 
C_LmaxTO_end = 1.8; 
L1 = C_LmaxTO_end - C_LmaxTO_begin;
% enter range for wing loading 
W_S_begin = 10; 
W_S_end = 60; 
L2 = W_S_end-W_S_begin;
n = 10; % incerement size
d1 = L1/(n-1); 
d2 = L2/(n-1);
C_LmaxTO = C_LmaxTO_begin:d1:C_LmaxTO_end;
W_S = W_S_begin:d2:W_S_end;
% Solve: 
TOP = 300;
for i = 1:length(C_LmaxTO)
    for j = 1:length(W_S)
        W_P(i,j) = TOP*sigma*C_LmaxTO(i)/W_S(j); 
    end
end
[X1,Y1] = meshgrid(W_S,W_P);
plot(W_S,W_P(:,1:10)','.-')  %changes made here

MATLAB: Curve fitting, setting domain/forcing asymptote

I can't think of a generic way to constrain a function to tend to infinity as x approaches 1, but you might have some luck defining a function that has that behavior and fitting it. For example:

load census                    % define some data having your shape
x = (cdate-1775)/10;
y = 1./pop;
ft = fittype('b1/((x-1)^b2)'); % has the desired asymptotic behavior
f = fit(x,y,ft,'start',[1 1])
plot(x,y,'bx', x,f(x),'r-')    % not a great fit, but it's a start

Best Answer

Related Solutions

MATLAB: Data curve fitting, connecting point

MATLAB: Curve fitting, setting domain/forcing asymptote

Related Question