Given that refers to learning rate and x refers i ith to the input to the neuron, Which of the followings most suitably describes the weight updation rule of a Kohonen SOM? (where ' j ' jth refers to the neuron in the lattice)

1. Aw_ij(new) = (1 − η)·w_ij(old) + η·x_i
2. Bw_ii(new) = η·w_ii(old) + (1 − η)·x_i
3. Cw_ij(new) = (1 − η)·w_ij(old) + x_i
4. Dw_ij(new) = w_ij(old) + η·x_i

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Correct answer: A. w_ij(new) = (1 − η)·w_ij(old) + η·x_i

Explanation

SOM moves the winning neuron's weights toward the input: w(new) = w(old) + η(x − w(old)) = (1 − η)·w(old) + η·x.