Consider a perceptron that has two real-valued inputs and an output unit with a step activation function. All the initial weights and the bias θ = 0.1. Assume the teacher has said that the output should be 0 for the input input1 = 5 and input2 = -3. Show how the perceptron learning rule would alter this neural network upon processing this training example. Let the learning rate, α = 0.2 and be sure to update the perceptron weights during training. Draw the network architecture before training begins. Show the training process. Using the same perceptron, predicts the outcome for new inputs, input1=10 and input2=5.

(a) Here is how the perceptron looks before the training starts:

Answered: Draw the network architecture before…

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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Consider a perceptron that has two real-valued inputs and an output unit with a step activation function. All the initial weights and the bias θ = 0.1. Assume the teacher has said that the output should be 0 for the input input1 = 5 and input2 = -3. Show how the perceptron learning rule would alter this neural network upon processing this training example. Let the learning rate, α = 0.2 and be sure to update the perceptron weights during training.