[NARX] How can I interpret the input weight with delay

Hi all, I have created a NARX neural network model using matlab with 4 exogenous variables, 2 delays and 3 hidden neurons.
After training,I want to retrieve the weights of each input and the corresponding delay input. By using net.IW{1}, i have returned the following output: >> net.IW{1}
ans =
0.0447 -0.2305 -0.6253 0.5424 -0.2860 -0.0664 -0.4632 -0.8809
0.0167 -0.1856 -0.1209 0.2211 -0.2072 -0.2291 -0.1980 -0.4857
0.0333 -0.1057 0.4207 -0.1289 -0.0046 -0.1781 0.0888 0.0221
which is 3X8.
So here is the question: for the 1st neuron, how can I interpret the 8 numbers? which of the 2 are correspond to the 1st exogenous variable? is it (0.0447 and -0.2305) or (0.0447 and -0.2860)

 Accepted Answer

To be consistent with matrix multiplication, it has to be (0.0447 and -0.2860)
h(t) = b1 + IW*[ x(:,t-1) ; x(:,t-2)]; % t = 3,4,...
y(t) = b2 + LW*h(t);
Hope this helps.
Thank you for formally accepting my answer
Greg

1 Comment

Hi I have 6 exogenous inputs with 2 delays and 6 hidden nodes.
I got matrix 12x6. Shouldn't it have to 18x6?
since the input will be x(t), x(t-1), x(t-2)?
Really appreciate your answer. Thank you.

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