Consider Self Organization Feature Map SOFM with two cluster units and five input Units. The weight vectors for the cluster units are:- W1 = (0.2, 0.6, 0.8, 0.2, 1.0) and W2 = (0.1, 0.2, 0.4, 0.7, 1.0) %3D Use the square of the Euclidean distance to find the winning cluster unit for the input Pattern x = (0.1, 1.0, 0.5, 0.0, 0.0). Using a learning rate of 0.5, find the new weights for the winning unit. %3D
Consider Self Organization Feature Map SOFM with two cluster units and five input Units. The weight vectors for the cluster units are:- W1 = (0.2, 0.6, 0.8, 0.2, 1.0) and W2 = (0.1, 0.2, 0.4, 0.7, 1.0) %3D Use the square of the Euclidean distance to find the winning cluster unit for the input Pattern x = (0.1, 1.0, 0.5, 0.0, 0.0). Using a learning rate of 0.5, find the new weights for the winning unit. %3D
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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