using a trained ANN

John Williams answered . 2024-12-21 00:32:38

 % FITNET REUSE EXAMPLE: 
 % Train in workspace
 % Save copy to directory
 % Clear original from workspace
 % Load copy from directory to workspace
 % Use copy on "new" data

% If it exists, delete netg from the directory

delete netg.mat

% Clear the workspace and plot before designing netg

 close all, clear all, clc
 [ x,t ] = simplefit_dataset;
 [ I N ] = size(x)        %[1 94]
 [ O N ] = size(t)        %[1 94]
 MSE00   = mean(var(t',1))% 8.3378

 subplot(2,1,1), hold on
 plot(x,'k'), plot(t,'b')
 subplot(2,1,2), hold on
 plot(x,t,'b')

% NOTE: t has 4 local extrema

 netg            = fitnet(4);
 rng(4151941)
 [ netg tr y e ] = train(netg,x,t);
 % y = netg(x); e = t-y;
 stopcriteria = tr.stop      % Validation stop
 NMSE         = mse(e)/MSE00 % 5.8958e-3
 R2           = 1-NMSE       % 0.9941
 plot(x,y,'r')

' netg is in workspace'

whos netg

'netg is not in directory'

dir netg 
dir netg.mat

'Save copy of netg to directory. Becomes netg.mat'

 save( 'netg')
 dir netg.mat

'Next clear original netg from workspace'

 whos netg
 clear netg
 whos netg

'Then load copy of netg from directory to workspace'

 load netg
 whos netg

'Delete copy of netg from directory'

 dir netg.mat 
 delete netg.mat
 dir netg.mat

'Apply netg copy in workspace to "new" data'

 ylr    = netg(fliplr(x));
 diffy  = minmax(ylr-fliplr(y)) % [ 0 0 ]

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