Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Fidelis Zanetti de Castro"'
Publikováno v:
Neural Networks. 122:54-67
In this paper, we address the stability of a broad class of discrete-time hypercomplex-valued Hopfield-type neural networks. To ensure the neural networks belonging to this class always settle down at a stationary state, we introduce novel hypercompl
In this paper, we first address the dynamics of the elegant multi-valued quaternionic Hopfield neural network (MV-QHNN) proposed by Minemoto and collaborators. Contrary to what was expected, we show that the MV-QHNN, as well as one of its variation,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f40a976fd4259ebe54d4e4316f30bfd4
http://arxiv.org/abs/2112.06643
http://arxiv.org/abs/2112.06643
Autor:
null Fabio Bermudes Cabral, null Bruno Cardoso Coutinho, null Fidelis Zanetti de Castro, null Mateus Barcellos Costa
Publikováno v:
Procedings do XV Simpósio Brasileiro de Automação Inteligente.
Publikováno v:
Proceeding Series of the Brazilian Society of Computational and Applied Mathematics.
In this paper, we review three discrete-time complex-valued Hopfield neural networks (CvMHNNs) proposed recently in the literature. Contrary to what has been stated, we provide examples in which the sequences produced by these CvMHNN fails to converg
Publikováno v:
Proceeding Series of the Brazilian Society of Computational and Applied Mathematics.
In this paper, we generalize the famous Hopfield neural network to unit octonions. In the proposed model, referred to as the continuous-valued octonionic Hopfield neural network (CV-OHNN), the next state of a neuron is obtained by setting its octonio
Publikováno v:
IJCNN
Multivalued quaternionic Hopfield neural networks (MV-QHNN) extend the widely known Hopfield network from {−1, +1} to unit quaternions. The first MV-QHNN model, introduced by Isokawa and collaborators, uses a multivalued signum function based on th