Answer this question Given the two input patterns p1 and p2 shown in the figure. Use row-major order to scan the patterns and each white square will be represented by a "-1", and each dark square will be represented by a "10". Compute the weight matrix W of an associative memory neural network using the pseudoinverse rule (Moore-Penrose pseudoinverse) with output targets t1=[31] and t2=[15]. Then determine if the network response (output) at for the given testing input pt shown in the figure is closer to t1 or t2 (note: first determine at=Wpt then compute distance). Given the input/output prototype vector pairs {p1=[1.110]T,t1=[11]}. {p2=[0.511]T,t2=[01]}, and {p3=[111]T,t3=[11]} use the pseudoinverse rule (Moore-Penrose pseudoinverse) to find the weights of the network W. Do not use normalized inputs. (note: W=TP+where P+=(PTP)1PT ). Select the correct answer A [26.6613e165.234.21.6653e16] B [39.992e167.84.56.32.498e16] C [0.666672.2204e161.733311.45.5511e17] E [0.266678.8818e170.693330.40.562.2204e17] [0.41.3323e161.040.60.843.3307e17]