Consider the very small neural network below, with 2 inputs and no biases, and with the activation function being the identity function, f(z)=z. The input (1, -1) is presented to the network, as illustrated. The layer 2 activations have been calculated, and are shown. Now, what are the layer 3 activations, i.e., the outputs? inputs 20 X₁=1 X₂=-1 a (1) = 1 (1) W12 w₁2=1 (1) = -1 W21 (1) W22 = =1 a(²) = 2 (2) W21 (2) W11 (2) W₁ a² = 1 = -1 1 W22 outputs a(³) a(³)

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Consider the very small neural network below, with 2 inputs and no biases, and with the
activation function being the identity function, f(z)=z. The input (1, -1) is presented to the
network, as illustrated. The layer 2 activations have been calculated, and are shown. Now, what
are the layer 3 activations, i.e., the outputs?
inputs
(1)
a₁ = 1
x₁=1
X₂=-1
(1, -2)
(1)
az = -1
(-2, 1)
(1, 2)
W12
(2, 1)
‚(1)_
W11
(1)
W22
W21
4
a₁
(2)
az
= 2
W21
(2)
W
12
= 1
(2)
Wil
=-1
= 1
W22
= -1
-
outputs
a₁ =?
(3)
az
Transcribed Image Text:Consider the very small neural network below, with 2 inputs and no biases, and with the activation function being the identity function, f(z)=z. The input (1, -1) is presented to the network, as illustrated. The layer 2 activations have been calculated, and are shown. Now, what are the layer 3 activations, i.e., the outputs? inputs (1) a₁ = 1 x₁=1 X₂=-1 (1, -2) (1) az = -1 (-2, 1) (1, 2) W12 (2, 1) ‚(1)_ W11 (1) W22 W21 4 a₁ (2) az = 2 W21 (2) W 12 = 1 (2) Wil =-1 = 1 W22 = -1 - outputs a₁ =? (3) az
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