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Perform 3 training steps of the Hebbian learning rules to find the optimal weights - 1 and the following using the continuous activation function f (net) = data specifying the initial weights W = 1; wg = -1; W = 0; W = 0.5, and the training inputs: 1+e-net X, X2 X X 1.5 0 -0.5 -2 -2 -1.5 -1 1.5 110

Perform 3 training steps of the Hebbian learning rules to find the optimal weights - 1 and the following using the continuous activation function f (net) = data specifying the initial weights W = 1; wg = -1; W = 0; W = 0.5, and the training inputs: 1+e-net X, X2 X X 1.5 0 -0.5 -2 -2 -1.5 -1 1.5 110

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Perform 3 trainingsteps of the Hebbian earing rues o fid the optimal weights using the continuous actlvation function f (net) = — 1and the following data specifyingthe initial welghts W = 1; Wi = ; WY =05 ,and the tralning Inputs: T,-m 7 X % | X[ X 1 -2 15 |¢ 1 [05[2 |15 0 1 -1 15
Perform 3 training steps of the Hebbian learning rules to find the optimal weights -1 and the following data specifying the initial weights W = 1; W = -1; W? = 0; W = 0.5 , and 2 using the continuous activation function f (net) =; 1+e-net %3D the training inputs: X, Xa X4 X, 1.5 -2 1 -0.5 -2 -1.5 1 -1 1.5
Transcribed Image Text:Perform 3 training steps of the Hebbian learning rules to find the optimal weights -1 and the following data specifying the initial weights W = 1; W = -1; W? = 0; W = 0.5 , and 2 using the continuous activation function f (net) =; 1+e-net %3D the training inputs: X, Xa X4 X, 1.5 -2 1 -0.5 -2 -1.5 1 -1 1.5
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