NEURAL NETWORK Computer Science Homework Help

NEURAL NETWORK ASSIGNMENT

  • Assume you want to classify the following four points (x1; x2) €IR2:

X1

0

0

1

1

X2

0

1

0

1

Class

C0

C0

C0

C1

  • Explain the simplest neural network that can classify the above points?
  • Consider the following points

Note:Fully specify all necessary parameters of a neural network that canclassify the points in Part (a) and draw the decision boundary.(6marks)

X1

0

0

1

1

X2

0

1

0

1

Class

C0

C1

C1

C0

Explain whether the network you provided in part (a) correctly classify these points. (4marks)

2. Back-propagation algorithm:

Consider the following neural network:

With configuration:-

1

1

1

1

1

-1

0.5

-0.5

-0.5

Performone iteration of the back propagation algorithm, assuming that thehidden layer and the output layer use the Log-Sigmoid activationfunction.

yk = —————————————————(1)

for inputs (x1; x2) = (0,1) and output y = 1. (6marks)

3.Prove that if the activation function of a 2 layered neural network isthe identity function, the neural network is equivalent to a simpleperceptron with a linear activation function.(4marks)

3 days ago

-15-


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