hdl:10013/epic.20866
Modeling time-varying processes by unfolding the time domain
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lkindermann [ at ] awi-bremerhaven.de
Abstract
Most current technologies in modeling time varyingprocesses aim to adapt a static model over time in whathas become to be known as continuous learning. Wepropose here a different approach to the same problemdomain that of including the time explicitly in themodeling. An example implementation of this strategy isgiven in form of a multilayer perceptron with explicit timeinput. The performance of this approach is evaluating on abenchmark that was constructed to illustrate typicalproblems in industrial applications.
Item Type
Conference
(Conference paper)
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Publication Status
Published
Event Details
Proceedings of the International Joint Conference on Neural Networks (IJCNN'99), Washington DC..
Eprint ID
10382
Cite as
Kindermann, L.
and
Trappenberg, T.
(1999):
Modeling time-varying processes by unfolding the time domain
,
Proceedings of the International Joint Conference on Neural Networks (IJCNN'99), Washington DC.
.
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