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?
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?
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
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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?
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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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