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- W2100668045 abstract "This paper proposes a discrete-time recurrent neural network architecture and parameter adaptation algorithm for modeling of nonlinear dynamic systems. The learning algorithm is based on variational calculus and operates off-line. A neural network based current transformer nonlinear model is presented as a demonstration of the proposed architecture and learning algorithm. It is designed for power engineering needs in power systems and is suited for real-time applications in digital relay protections." @default.
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- W2100668045 date "2004-10-26" @default.
- W2100668045 modified "2023-09-23" @default.
- W2100668045 title "Modeling of nonlinear dynamic systems via discrete-time recurrent neural networks and variational training algorithm" @default.
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- W2100668045 doi "https://doi.org/10.1109/is.2004.1344645" @default.
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