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Can anyone explain why the answer for both problems below is D In an artificial

ID: 3817650 • Letter: C

Question

Can anyone explain why the answer for both problems below is D

In an artificial neural network, which of the following pairs of input connection weights would cause a neuron with two inputs and a threshold value of 3 to produce an output of 1 only when both of its inputs are 1?

                A. 0, 0                   B. 2, 0                   C. 0, 2                   D. 2, 2

ANSWER: D

In an artificial neural network, which of the following pairs of input connection weights would cause a neuron with two inputs and a threshold value of 2 to produce an output of 0 only when both of its inputs are 0?

A. 0, 0                   B. 3, 0                   C. 0, 3                   D. 3, 3

ANSWER: D

Explanation / Answer

when both inputs are labelled to 1 then threshhold value decresed by 1. so, (X,Y)=(3,3)------>(2,2)

when both inputs are labelled to 0 then threshhold value increased by 1. so, (X,Y)=(2,)-------->(3,3)

so, both options are D

If the output of a particular training case is labelled 1 when it should be labelled 0, the threshold value (theta) is increased by 1, and all weight values associated with inputs of 1 are decreased by 1. The opposite is performed if the output of a training case is labelled 0 when it should be labelled 1. No changes are made to the threshold value or weights if a particular training case is correctly classified

equation can be

(eqn 1)
If OUTPUT = 1, but should be 0
then {theta = theta + 1}
and {weightx = weightx -1, if inputx = 1}

(eqn 2)
If OUTPUT = 0, but should be 1
then {theta = theta - 1}
and {weightx=weightx +1, if inputx = 1}

Description:

x refers to a particular input-node and weight pair.equation (1), increasing the threshold value serves to make it less likely that the same sum of products will exceed the threshold in later training iterations, and thus makes it less likely that an output value of 1 will be produced when the same inputs are presented.

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