Sigmoid function flu)= logsiglu) and its derivative f(u=dlogsiglu) Neural Networks ch9, ver. 9b 1+e-m1+e or simplicity set B df(u) http://mathworld.wolframcom/sigmoidFunctionhtml note Logistic sigmoid(logsig) au dx https://kawahara.ca/how-to-compute-the-derivative-of-a- hence sigmoid-function-fully-worked-examplel df(a)(1+e“丿d(1+e 1/(1+e) f(u)= (using chain rule) htd(1+e“)a e e e +e-)}+e (1+e)(1+e“)(1+e-“) +e f()-f(l) e us (n)=f(l)-f(n) http:/ink.springercom/chapter/10.1007%2b3-540-59497-3175#page-1,httpsimiloainfwordpresscom/2013/11/06/rectifier-nonlinearities/Sigmoid function f(u)= logsig(u) and its derivative f’(u)=dlogsig(u) • Neural Networks Ch9. , ver. 9b 18   ( ) ( ) ( )(1 ( )) ( ) Thus, ( ) 1 ( ) (1 ) 1 1 (1 ) 1 (1 ) (1 ) (1 ) (1 ) 1 (1 ) (1 ) 1 (1 ) 1 ( ) (1 ) 1 ( ) ,(using chain rule) (1 ) (1 ) 1 1 ( ) ( ) ( ) ( ) , for simplicity set 1 1 1 1 1 ( ) ' 2 2 ' ' ' f u f u f u du df u f u f u e e e e e e e e e e e e e e f u du d e d e e d du df u f u Hence f u du df u e e f u u u u u u u u u u u u u u u u u u u u = = − = −       + − + = + + − + + + = + + = + − = + − = + +       + = = = = + = + = − − − − − − − − − − − − − − − − − − −   http://link.springer.com/chapter/10.1007%2F3-540-59497-3_175#page-1 , https://imiloainf.wordpress.com/2013/11/06/rectifier-nonlinearities/ http://mathworld.wolfram.com/SigmoidFunction.html Logistic sigmoid (logsig) https://kawahara.ca/how-to-compute-the-derivative-of-a￾sigmoid-function-fully-worked-example/ x x e dx de note : =