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In the following Multi-Layer Architecture there are 6 different neurons. The input signals of neurons are initialized with il = 2, i2 = -1 and synaptic weights of the neurons are also initialized w1 1, w2 = -5, w3 = -3, w4 = 6, w5 = -5, w6 = -4, w7=-2, w8 = -3 respectively with bias values b1 = b2 = -1. Compute the output of two hidden neurons h1, h2 and two output neurons ol, o2 using forward pass / function signal. Use logistic function with a =1. %3! %3D %3D w1 w5 i1 h1 01 w2 w6 w3 12 h2 02 w4 w8 b1 b2 1

In the following Multi-Layer Architecture there are 6 different neurons. The input signals of neurons are initialized with il = 2, i2 = -1 and synaptic weights of the neurons are also initialized w1 1, w2 = -5, w3 = -3, w4 = 6, w5 = -5, w6 = -4, w7=-2, w8 = -3 respectively with bias values b1 = b2 = -1. Compute the output of two hidden neurons h1, h2 and two output neurons ol, o2 using forward pass / function signal. Use logistic function with a =1. %3! %3D %3D w1 w5 i1 h1 01 w2 w6 w3 12 h2 02 w4 w8 b1 b2 1

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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2. In the following Multi-Layer Architecture there are 6 different neurons. The input signals of neurons are initialized with il = 2, i2 = -1 and synaptic weights of the neurons are also initialized w1 1, w2 = -5, w3 = -3, w4 6, w5 = -5, w6 = -4, w7=-2, w8 = -3 respectively with bias values b1 = b2 = -1. Compute the output of two hidden neurons h1, h2 and two output neurons o1, 02 using forward pass / function signal. Use logistic function with a =1. w1 w5 11 h1 01 w2 w6 w3 w7 12 h2 02 w4 w8 b1 b2 1 1
Transcribed Image Text:2. In the following Multi-Layer Architecture there are 6 different neurons. The input signals of neurons are initialized with il = 2, i2 = -1 and synaptic weights of the neurons are also initialized w1 1, w2 = -5, w3 = -3, w4 6, w5 = -5, w6 = -4, w7=-2, w8 = -3 respectively with bias values b1 = b2 = -1. Compute the output of two hidden neurons h1, h2 and two output neurons o1, 02 using forward pass / function signal. Use logistic function with a =1. w1 w5 11 h1 01 w2 w6 w3 w7 12 h2 02 w4 w8 b1 b2 1 1
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