Abstract
This work shows the use of a novel neural model for identification of non-linear process. The neural model make use of internal dynamic with dynamical neurons. The parameters responsible for the dynamic of the neural net are adjustable, giving a high flexibility for the neural model in process identification.
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© 1998 Springer-Verlag Wien
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de Oliveira, R.C.L., de Azevedo, F.M., Barreto, J.M. (1998). Dynamic Neural Nets in the State Space Utilized in Non-Linear Process Identification. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6492-1_130
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DOI: https://doi.org/10.1007/978-3-7091-6492-1_130
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-83087-1
Online ISBN: 978-3-7091-6492-1
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