Question: # 1 Consider the back - propagation numerical example on lecture notes. The weighting matrices Z between input layer and hidden layer, W between hidden

1

Consider the back

-

propagation numerical example on lecture notes. The weighting matrices

Z

between input layer and hidden layer,

W

between hidden layer and output layer was updated with backpropagation process. Now train with the updated weighting matrix from input to supervisor. Namely, compute the response

h,

activation a

,

and estimation error

t - f (a)

as outlined in the following diagram. Discuss how does this error compare to the result from the initial forward process without backpropagation. Would you recommend more back

-

propagation iterations to reduce the errors?

# 1 Consider the back - propagation numerical

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