Aspire Faculty ID #14712 · Topic: UGC NET Computer Science 26 June 2025 (Paper II) · Just now
UGC NET Computer Science 26 June 2025 (Paper II)

Consider the following table defining the sample inputs and corresponding target values for a perceptron model.

Sample No x1 x2 target w1 w2
S100000
S2011
S3101
S4111

What shall be the value of updated weights after applying all the samples S1 to S4 (in the order S1, S2, S3, S4) to this model. Given that the initial weights w1=0, w2=0, learning rate=0.1 and no bias is involved in the perceptron. The activation function for this perceptron is given below:

yobserved = { 1 if yin > 0
0 if yin < 0 }

  1. w1 = 0.1, w2 = 0.1
  2. w1 = 0.0, w2 = 0.2
  3. w1 = 0.0, w2 = 0.1
  4. w1 = 0.2, w2 = 0.2

Solution

Using perceptron learning rule: Δw = η (t − y) x, where y = 1 if yin > 0 else 0.

S1 (0,0,t=0): yin=0 ⇒ y=0 ⇒ no change ⇒ (w1,w2)=(0,0)

S2 (0,1,t=1): yin=0 ⇒ y=0 ⇒ Δw=0.1(1−0)(0,1) ⇒ (w1,w2)=(0,0.1)

S3 (1,0,t=1): yin=0 ⇒ y=0 ⇒ Δw=0.1(1−0)(1,0) ⇒ (w1,w2)=(0.1,0.1)

S4 (1,1,t=1): yin=0.1+0.1=0.2>0 ⇒ y=1 ⇒ no change

Final Weights: w1=0.1, w2=0.1

Answer: (1)

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