Data processing: artificial intelligence – Neural network – Learning task
Reexamination Certificate
2008-01-01
2008-01-01
Hirl, Joseph P. (Department: 2129)
Data processing: artificial intelligence
Neural network
Learning task
C706S015000, C706S019000
Reexamination Certificate
active
11396868
ABSTRACT:
Method and apparatus for training a system model with gain constraints. A method is disclosed for training a steady-state model, the model having an input and an output and a mapping layer for mapping the input to the output through a stored representation of a system. A training data set is provided having a set of input data u(t) and target output data y(t) representative of the operation of a system. The model is trained with a predetermined training algorithm which is constrained to maintain the sensitivity of the output with respect to the input substantially within user defined constraint bounds by iteratively minimizing an objective function as a function of a data objective and a constraint objective. The data objective has a data fitting learning rate and the constraint objective has constraint learning rate that are varied as a function of the values of the data objective and the constraint objective after selective iterative steps.
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Gerules Mark
Hartman Eric Jon
Piche Stephen
Hirl Joseph P.
Hood Jeffrey C.
Meyertons Hood Kivlin Kowert & Goetzel P.C.
Pavilion Technologies, Inc.
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