2. Apply the back propagation algorithm for the given layer network. Calculate the value of error signal in the given MLP were xl = 1.5, x2 = -2.3, wl=1, w2 = -2.8, w3 = -1.6, w4 = 2, br= -1 and sigmoid as activation function for each neuron. N N Output N

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. Apply the back propagation algorithm for the given layer network. Calculate the value of
error signal in the given MLP were xl = 1.5, x2 = -2.3, wl=1, w2 = -2.8, w3 = -1.6, w4 =
2, bk= -1 and sigmoid as activation function for each neuron.
N
Output
N
Transcribed Image Text:2. Apply the back propagation algorithm for the given layer network. Calculate the value of error signal in the given MLP were xl = 1.5, x2 = -2.3, wl=1, w2 = -2.8, w3 = -1.6, w4 = 2, bk= -1 and sigmoid as activation function for each neuron. N Output N
1. Solve the AND problem for multi-layer perceptron and apply each neuron threshold as
activation function.
Output
N
N
Input layer
hidden layer
Output layer
2. Apply the back propagation algorithm for the given layer network. Calculate the value of
error signal in the given MLP were x1 = 1.5, x2 = -2.3, wl=1, w2 = -2.8, w3 = -1.6, w4 :
Transcribed Image Text:1. Solve the AND problem for multi-layer perceptron and apply each neuron threshold as activation function. Output N N Input layer hidden layer Output layer 2. Apply the back propagation algorithm for the given layer network. Calculate the value of error signal in the given MLP were x1 = 1.5, x2 = -2.3, wl=1, w2 = -2.8, w3 = -1.6, w4 :
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