Recognition of facial expressions - Knowledge Based Systems ...
Recognition of facial expressions - Knowledge Based Systems ...
Recognition of facial expressions - Knowledge Based Systems ...
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defined as:<br />
∆w<br />
= −η<br />
∇<br />
ji<br />
ji<br />
∂E<br />
E = −<br />
∂w<br />
ji<br />
The gradient components can be expressed as follows:<br />
∂E<br />
∂w<br />
ji<br />
∂E<br />
=<br />
∂a<br />
j<br />
∂a<br />
j<br />
∂net<br />
j<br />
∂net<br />
∂w<br />
ji<br />
j<br />
The third partial derivative in the previous equation can be easily computed based on the<br />
definition <strong>of</strong><br />
∂ net<br />
j<br />
∂net<br />
∂w<br />
ji<br />
j<br />
=<br />
∂<br />
∂w<br />
ji<br />
k<br />
w<br />
jk<br />
a<br />
k<br />
=<br />
k<br />
∂w<br />
jk<br />
∂w<br />
a<br />
ji<br />
k<br />
Using the chain rule the previous relation can be written as:<br />
∂net<br />
∂w<br />
ji<br />
j<br />
=<br />
k<br />
∂w<br />
(<br />
∂w<br />
jk<br />
ji<br />
a<br />
k<br />
+ w<br />
jk<br />
∂a<br />
∂w<br />
k<br />
ji<br />
)<br />
Examining the first partial derivative, it can be noticed that<br />
∂w<br />
∂w<br />
jk<br />
ji<br />
is zero unless k = i .<br />
Furthermore, examining the second partial derivative, if w<br />
jk<br />
is not zero, then there<br />
∂ak<br />
exists a connection from unit k to unit j which implies that must be zero<br />
∂w<br />
because otherwise the network would not be feed-forward and there would be a recurrent<br />
connection.<br />
Following the criteria,<br />
ji<br />
∂net<br />
∂w<br />
ji<br />
j<br />
= a<br />
i<br />
The middle partial derivative is<br />
∂a<br />
j<br />
∂net<br />
j<br />
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