Appeal No. 1999-1856
Application No. 08/686,792
BACKGROUND
The appellants’ invention relates to a learning process for a neural network. An
understanding of the invention can be derived from a reading of exemplary claims 15
and 16, which are reproduced below.
15. A method for controlling an industrial process using a neural
network, the industrial process having at least one time-variable
parameter, the neural network including a control network and a
background network, the method comprising the steps of:
training the control network using current process data to generate
a current process model;
training the background network using representative process data
to generate an averaged process model of the industrial process over a
predetermined time period;
determining a parameter of the at least one time-variable
parameter of the industrial process using the current process model, and
controlling the industrial process as a function of the determined
parameter.
16. A method for controlling an industrial process using a neural
network, the industrial process having at least one time-variable
parameter, the neural network including a control network and a
background network, the method comprising the steps of:
training the control network using current process data to generate
a current process model;
training the background network using representative process data
to generate an averaged process model of the industrial process over a
predetermined time period;
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