Consider the neural network shown below. The network consists of 2 input values (x1, x2) with their associated weights (0.3, 0.4, 0.3) and (0.2, 0.7, 0.1), 3 nodes in the hidden layer (h1, h2, h3) with associated weights (0.3, 0.5, 0.2) for target output. Assume all neurons have the same bias b = 0.2, and the same sigmoid activation function.   If we input (x1, x2) = [1, 2], what will be the network’s output?

Principles of Information Systems (MindTap Course List)
12th Edition
ISBN:9781285867168
Author:Ralph Stair, George Reynolds
Publisher:Ralph Stair, George Reynolds
Chapter7: The Internet, Web, Intranets, And Extranets
Section7.6: Information Systems @ Work: Improved Insight Via Clickstream Analysis
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Consider the neural network shown below. The network consists of 2 input values (x1, x2) with their associated weights (0.3, 0.4, 0.3) and (0.2, 0.7, 0.1), 3 nodes in the hidden layer (h1, h2, h3) with associated weights (0.3, 0.5, 0.2) for target output. Assume all neurons have the same bias b = 0.2, and the same sigmoid activation function.

 

If we input (x1, x2) = [1, 2], what will be the network’s output?

hi
0.3
0.3
X1
0.4
Q.3
0.5
0.2
h2
0.7
X2
0.1
0.2
h3
Transcribed Image Text:hi 0.3 0.3 X1 0.4 Q.3 0.5 0.2 h2 0.7 X2 0.1 0.2 h3
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