# The Number of coefficents of Time delay neural network

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Abdelwahab Afifi on 27 Jan 2020
for the following Time delay neural network
clc; clear all; close all;
[X,T] = simpleseries_dataset;
net1 = timedelaynet(1:2,20);
[Xs,Xi,Ai,Ts] = preparets(net1,X,T);
net1 = train(net1,Xs,Ts,Xi);
y1 = net1(Xs,Xi);
view(net1)
weights1 = getwb(net1)
According to my understanding; the input to this network supposed to be the current input and the previous inputs X(n), X(n-1), X(n-2)
Hence the number of weights supposed to be (3x20 +20x1) and the bias (20+1) , hence the vector od weights and bias suppoed to a vector with length = 101
But, when I use the getwb(net1) I get vector with length = 81 ??!!
why he neglect the weights of one sample

Mahesh Taparia on 4 Feb 2020
Hi
It does not neglect any weight. Since the number of input delays is 2, the number of weights will be (2X20+20X1) and the bias (20+1). The vector length will be 81. If the input delay is 3, then it will be 101. For more information you can refer to the documentation page of timedelaynet here.
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Abdelwahab Afifi on 4 Feb 2020
In case of delay =2, then which of the following will the input of the network ?
1- X(n), X(n-1) and X(n-2)
2- or X(n), X(n-1)

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