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a) Consider a 2 inputs NAND gate and simulate a perceptron algorithm for it. Where, learning rate=.02 and threshold = .2 b) Consider the above problem 3(a) in multilayer neural network with 2 hidden layers of size 3 and 3 respectively. Now draw the network.

a) Consider a 2 inputs NAND gate and simulate a perceptron algorithm for it. Where, learning rate=.02 and threshold = .2 b) Consider the above problem 3(a) in multilayer neural network with 2 hidden layers of size 3 and 3 respectively. Now draw the network.

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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3. a) Consider a 2 inputs NAND gate and simulate a perceptron algorithm for it. Where, learning rate=.02 and threshold = .2 b) Consider the above problem 3(a) in multilayer neural network with 2 hidden layers of size 3 and 3 respectively. Now draw the network.
Transcribed Image Text:3. a) Consider a 2 inputs NAND gate and simulate a perceptron algorithm for it. Where, learning rate=.02 and threshold = .2 b) Consider the above problem 3(a) in multilayer neural network with 2 hidden layers of size 3 and 3 respectively. Now draw the network.
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