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Publikováno v:
Neurocomputing. 233:104-115
In this paper we present a Complex-Valued Recurrent Neural Network (CVRNN), trained with a recursive Levenberg-Marquardt (LM) learning algorithm in the complex domain, applying it to the problem of dynamic system identification, and to an adaptive ne
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319270593
MICAI (1)
MICAI (1)
The present article gives an extension of the real-valued recurrent neural network topology and its Back-Propagation (BP) learning to the complex-valued one. The BP learning is achieved by the use of diagrammatic rules to obtain the adjoint recurrent
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::103f8f2a793fdf5fa20c0ac051ebc4e2
https://doi.org/10.1007/978-3-319-27060-9_27
https://doi.org/10.1007/978-3-319-27060-9_27