Teaching UGC NET Mock Test Series 2025 (Paper 1 & 2) Artificial Intelligence Artificial Neural Network
Let Wij represents weight between node i at layer k and node j at layer (k – 1) of a given multilayer perceptron. The weight updation using gradient descent method is given by
Where α and E represents learning rate and Error in the output respectively.
1
\({W_{ij}}\left( {t + 1} \right) = {W_{ij}}\left( t \right) + \alpha \frac{{\partial E}}{{\partial {W_{ij}}}},\;0 \le \alpha \le 1\)
2
\({W_{ij}}\left( {t + 1} \right) = {W_{ij}}\left( t \right) - \alpha \frac{{\partial E}}{{\partial {W_{ij}}}},\;0 \le \alpha \le 1\)
3
\({W_{ij}}\left( {t + 1} \right) = \alpha \frac{{\partial E}}{{\partial {W_{ij}}}},\;0 \le \alpha \le 1\)
4
\({W_{ij}}\left( {t + 1} \right) = - \alpha \frac{{\partial E}}{{\partial {W_{ij}}}},\;0 \le \alpha \le 1\)