hopefully a clearer version of neural network. with actual weights
Post on 22-Dec-2015
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TRANSCRIPT
Hidden Layer Computation
• Xi =iW1 = • 1 * 1 + 0 * -1 = 1, • 1 * -1 + 0 * 1 = -1 = • { 1 - 1} = {Xi1,Xi2} = Xi
xF
1
1
• h = F(X)• h1 = F(Xi1) = F(1)• h2 = F(Xi2) = F(-1)
27.01
1
1
1)2(
73.01
1
1
1)1(
)1(2
)1(1
xi
xi
XiF
XiF
Error
• D= Output(1 – Output)(Target – Output)• Target T1 = 1 , O1 = 0.325 = 0.33
• d1 = 0.33( 1 -0.33)(1 -0.33 ) = 0.33 (0.67)(0.67) = 0.148
Weight Adjustment
• △W2t = α hd + Θ △W2t-1
• where α = 1• Time t = 1 so no previous time
�
dh
dhd
h
hhd
22
111
2
1
)15.0*27.0(
)15.0*73.0(15.0
27.0
73.0hd
This equals
• e1 = (h1(1-h1)W11 D1• e2 = (h2(1-h2)) W21 D1 • d1 = 0.15e1 = (0.73(1-0.73))( -1* 0.15 )• e2 =( 0.27(1-0.27)) (0 *0.15 )
• e1 = (0.73(0.27)( -0.15))• e2 =( 0.27(0.73)) (0)• e1 = -0.03• e2 = 0
Weight Adjustment
• △W1t = α Ie + Θ △W2t-1
• where α = 1
2212
211121
2
1
eIeI
eIeIee
I
IIe
)0*0()03.0*0(
)0*1()03.0*1(003.0
0
1Ie