Reference no: EM131310579
Suppose that we have the following three reference patterns and their targets:
The probability of vector p1 is 0.25, the probability of vector p2 is 0.25 and the probability of vector p3 is 0.5.
i. Draw the network diagram for an ADALINE network with no bias that could be trained on these patterns.
ii. Sketch the contour plot of the mean square error performance index.
iii. Show the optimal decision boundary (for the weights that minimize mean square error) and verify that it separates the patterns into the appropriate categories.
iv. Find the maximum stable learning rate for the LMS algorithm. If the target values are changed from 26 and -26 to 2 and -2, how would this change the maximum stable learning rate?
v. Perform one iteration of the LMS algorithm, starting with all weights equal to zero, and presenting input vector p1. Use a learning rate of a = 0.5.
vi. Sketch the trajectory of the LMS algorithm on your contour plot. Assume a very small learning rate, and start with all weights equal to zero.
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What is the maximum stable learning rate
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