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A multilayer perceptron network for a two-class classification problem is given below. The units at the hidden and output layers are sigmoid (sign) functions. The

A multilayer perceptron network for a two-class classification problem is given below. The units at the hidden and output layers are sigmoid (sign) functions. The weights determined through training are: W00=0.5; W01=1, WO2=0.7; W03=1; W045-0.6; W05=1; W10=-0.5; W11=-1; W12=1. Input Layer Hidden Layer Output Layer x2 WOS W04 WO3 Output W02 WO1 wo (a) [7 points) Classify (x1,x2)=(0,0) (b) [8 points) Classify (x1,x2)=(1,1)

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