\documentclass[10pt]{article}

\begin{document}

\begin{itemize}

\item Apply inputs to the network, here subscript p is used as
the pattern index.
\[      x_{p} = (x_{p1},x_{p2},...,x_{pn})^{t} \]
\item Calculate, the inputs to the hidden layer units (see
figure 1)
\[ net_{pj}^{h} =  \sum_{i=1}^{N} w_{ji}^{h} x_{pi} +
\Theta_{j}^{h} \]
\item Calculate the outputs of the hidden layer units. 
\[      i_{pj} = f_{j}^{h}(net_{pj}^{h})  \]
\item Calculate the inputs to each output layer unit 
\[ net_{pk}^{o} =  \sum_{j=1}^{L} w_{kj}^{o} x_{pj} +
\Theta_{k}^{o} \]
\item Calculate output 
\[      o_{pk} = f_{k}^{o}(net_{pk}^{o}) \]
\item Calculate the error terms for the output units
\[     \delta_{pk}^{o} = (y_{pk}-o_{pk})
f_{k}^{o'}(net_{pk}^{o}) \]
\item Calculate the error terms for the hidden layer units
\[  \delta_{pj}^{h} = f_{j}^{h'}(net_{pj}^{h}) \sum_{k}
\delta_{pk}^{o} w_{pk}^{o} \]

Error terms on the hidden layer units are calculated before
updating the connection 
weights to the output layer units.

\item Calculate the weight updated between the output-hidden
layer units
\[ w_{kj}^{o}(t+1) = w_{kj}^{o}(t) + \eta
\delta_{pk}^{o}i_{pj} \]
\item Calculate the weight updates between the hidden-input
layer units
\[ w_{ji}^{h}(t+1) = w_{ji}^{h}(t) + \eta \delta_{pj}^{h}x_{i}
\]

\end{itemize}

The error term is calculated as :

\[  E_{p} = \frac{1}{2} \sum_{k=1}^{M} \delta_{pk}^{2}  \]

In the procedure above, {\it i} is used as an index for the
input layer units,
{\it j} as an index for the hidden layer units and {\it k} as
an index
over the output layer units.  \\

\end{document}

