2) SOM algorithm based on unsupervised learning with input matrix i1 = (0.2; 0.7), i2 = (0.4; 0.5), i3 = (0.3; 0.2) The weight matrix is as shown in the figure. a) Calculate the set uj that fulfills the Kohonen neighborhood condition. b) If the initial learning coefficient is 0.2, find the new weights for uj. c) If learning continues, calculate the new weights for uj-1 and uj +1. 0.3;0.24 1 42 0.7; 0.2 0.9:02 0.2;0.2 0.5;9.4 0.5; 0.7 0.1,0.2 0.2;0.2u 43 0.3.0.5 12 0.4.0.4 0.6;0.3 13 0.7:0.8 44