Perform two training steps for the network as shown in figure given using the perceptron learning rule. Assume the training data 2. Xj = 1 d1 =0 X2 = [2 d2 =1 .2. And the initial weight vector w¡ = with learning constant c = .5 ip1 W1 W 2 ip: f(net) net W 3 ip 3 AWi d; Learning Signal r X;
Perform two training steps for the network as shown in figure given using the perceptron learning rule. Assume the training data 2. Xj = 1 d1 =0 X2 = [2 d2 =1 .2. And the initial weight vector w¡ = with learning constant c = .5 ip1 W1 W 2 ip: f(net) net W 3 ip 3 AWi d; Learning Signal r X;
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Transcribed Image Text:Perform two training steps for the network as shown in figure given using the perceptron learning rule. Assume the
training data
2.
Xj =
1
d1 =0
X2 = [2
d2 =1
.2.
And the initial weight vector w¡ =
with learning constant c = .5
Transcribed Image Text:ip1
W1
W 2
ip:
f(net)
net
W 3
ip 3
AWi
d;
Learning
Signal
r
X;
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