Architecture: Exercise 3(continue)(write formulas for A1/j=4). (4) How many inputs, hidden neurons, outputs, weights and biases in each layer? A1(=1)= 1+eb(a1/=)+0(=2=1)++bG=可A2(k=1)= 1+elo(j=1k=1)4(k=)+2(=2k=1)4(k=1)++b1k=1 P(=1)o21(=1j=1) Al (i=1k=1) 1P(=2)o24(=2j=1) /Neuron i=1 A1(=1 A2 6 =2(i=2, k=1)/ Neuron k=1 Bias=b1(i=1 Bias=b2(k=1 1pP(=9.oG=9=1) 1A5 01=2(=5k=1 2(k=2 P(-1) A10=1)42(1k=1) P(i=2)○ m=4(i=2j=1 ○4242 (=2k P(i=3) Q21(=3=4 2(=5k=3)A2ayer2,3 Output neurons A1(j=5) indexed by k A1: Hidden layer1=5 W=2=5X3 neurons, indexed by j b/=2=3x1 nput: Layer 1=1 W=1=9X5 Layer =2 P=9X1 b=1=5×1 <S2 generated Indexed by j <S1 generated Neural Networks Ch9. ver. 9b °26Architecture : Exercise 3 (continue) (write formulas for A1(j=4). How many inputs, hidden neurons, outputs, weights and biases in each layer? • Neural Networks Ch9. , ver. 9b 26 Input: P=9x1 Indexed by j A1: Hidden layer1 =5 neurons, indexed by j Wl=1=9x5 b l=1=5x1 l=1 (i=1,j=1) l=1 (i=2,j=1) l=1 (i=9,j=1) P(i=1) P(i=2) P(i=3) : : P(i=9)  ( 1, 1) ( 2, 1) ... b (j 1) 1 2 1 1 1 1 1 1 A ( 1) − = = + = = + + = = = + = = l i j P l i j P e j   A1 (i=1) P(i=1) P(i=2) P(i=9) Neuron i=1 Bias=b1(i=1)  l=2 (i=1,k=1)  l=2 (i=2,k=1)  l=2 (i=5,k=1) [ ( 1, 1) ( 1) ( 2, 1) ( 1) ... b ( 1)] 2 2 2 2 1 2 1 1 A ( 1) − = = = + = = = + + = = = + = = j k A k j k A k k l l e k   A2(k=2) A1 A2 A5 Neuron k=1 Bias=b2(k=1) l=1 (i=1,j=1) l=1 (i=2,j=1) l=1 (i=9,j=5) l=1 (i=3,j=4) A1(j=5) A1(j=1) A2:layer2, 3 Output neurons indexed by k Wl=2=5x3 b l=2=3x1 l=2(j=5,k=3) l=2(j=1,k=1) l=2(i=2,k=2) l=2(j=2,k=1) A1(j=2) Layer l=1 Layer l=2 S2 generated S1 generated