Hai
i want to implement back propagation algorithm in matlab.
the algorithm is follows
1.Apply input to the input units
2.Calculate the net-input values to the hidden layer units.
3.Calculate the outputs from the hidden layer.
4.Calculate the net-input values to the output layer units.
5.Calculate output from the output units.
6.Calculate the error term for the output units using.
New δopk=1+exp [(Ypk-Opk)2].fo’k(netopk), if (Y-O)>=zero
7.Calculate the error term for the hidden units,through applying Newδ°pk, also
New δopk=-{1+exp [(Ypk-Opk)2].fo’k(netopk)}, if (Y-O) <=zero
8.Update the weights on the output layer .
Wokj(t+1) =Wokj(t)+(η.Newδopk.ipj).
9.Update the weights on the hidden layer.
Whji(t+1) =Whji(t) + (η.Newδhpj.Xi).
Repeat steps from step 1 to step 9 until the error( Ypk-Opk)is acceptably small For each training vectors
on implementing this the error increases instead decreasing,i want the respective change in step 6 and 7 to get decrease the error.