Converged neural network states

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Hi -
I am wondering why I don’t arrive at the same trained network (net1f and net3f) even though I believe I have started from the same initial network state.
clear all, pack [x,t] = simplefit_dataset;
%% 1st trial net1i = feedforwardnet( 1); net1i= configure( net1i, x, t) ; IW1i= net1i.IW ; LW1i= net1i.LW ; b1i= net1i.b ; net1f = trainscg( net1i, x, t); IW1f= net1f.IW ; LW1f= net1f.LW ; b1f= net1f.b ;
%% 3rd trial with controlled initialization net3i = feedforwardnet( 1); net3i= configure( net3i, x, t) ; net3i.IW= IW1i ; net3i.LW= LW1i ; net3i.b= b1i ; net3f = trainscg( net3i, x, t); IW3f= net3f.IW ; LW3f= net3f.LW ; b3f= net3f.b ;
I appreciate your help.
Thanks. Siva

采纳的回答

Greg Heath
Greg Heath 2015-4-23
You have to explicitly reset the RNG state to the same initial value. To illustrate this. Check the RNG state before each training.
Hope this helps.
Greg.

更多回答(1 个)

Siva
Siva 2015-4-23
Thanks Greg!
Siva

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