Consider a 2D Gaussian mixture probability density function p=31N2(1,)+31N2(2,)+31N2(3,) Given 1=[00]T,2=[01]T,3=[20]T, and =[1001] 1. Following observations are drawn from equation (1): x1=[11]T,x2=[21]T,x3= [12]T,x4=[11]T,x5=[21]T,x6=[21]T. Classify the observations using the Bayes' decision rule. 2. If the probability function (1) is changed to p=0.4N2(1,I)+0.6N2(3,I), then check whether the decision of classification for observations x4 and x6 remain the same as done in part (1) or not