Storage capacity of a Potts-perceptron
J. Phys. I France, 1 8 (1991) 1109-1121
Article cité par
La fonctionnalité Article cité par… liste les citations d'un article. Ces citations proviennent de la base de données des articles de EDP Sciences, ainsi que des bases de données d'autres éditeurs participant au programme CrossRef Cited-by Linking Program. Vous pouvez définir une alerte courriel pour être prévenu de la parution d'un nouvel article citant " cet article (voir sur la page du résumé de l'article le menu à droite).
Article cité :
Citations de cet article :
q-state Potts-glass neural network based on pseudoinverse rule
Daxing Xiong and Hong ZhaoPhysical Review E 82 (2) (2010)
https://doi.org/10.1103/PhysRevE.82.026114
554 (2009)
https://doi.org/10.1109/AICI.2009.472
Q-nary pattern identifier based on committee of vector perceptrons
V. M. KryzhanovskyOptical Memory and Neural Networks 18 (3) 188 (2009)
https://doi.org/10.3103/S1060992X09030084
Artificial Neural Networks – ICANN 2009
Vladimir KryzhanovskyLecture Notes in Computer Science, Artificial Neural Networks – ICANN 2009 5768 844 (2009)
https://doi.org/10.1007/978-3-642-04274-4_87
A new design method for the complex-valued multistate hopfield associative memory
M.K. Muezzinoglu, C. Guzelis and J.M. ZuradaIEEE Transactions on Neural Networks 14 (4) 891 (2003)
https://doi.org/10.1109/TNN.2003.813844
Optimal capacity of the Blume-Emery-Griffiths perceptron
D. Bollé, I. Pérez Castillo and G. ShimPhysical Review E 67 (3) 036113 (2003)
https://doi.org/10.1103/PhysRevE.67.036113
Optimal colored perceptrons
D. Bollé and P. KozłowskiPhysical Review E 64 (1) 011915 (2001)
https://doi.org/10.1103/PhysRevE.64.011915
On the parallel dynamics of the diluted clock neural network
Daniel Gandolfo, Jean Ruiz and Valentin A. ZagrebnovPhysica A: Statistical Mechanics and its Applications 208 (3-4) 305 (1994)
https://doi.org/10.1016/0378-4371(94)00058-1
Storage capacity and optimal learning of Potts-model perceptrons by a cavity method
F Gerl and U KreyJournal of Physics A: Mathematical and General 27 (22) 7353 (1994)
https://doi.org/10.1088/0305-4470/27/22/012
The statistical mechanics of learning a rule
Timothy L. H. Watkin, Albrecht Rau and Michael BiehlReviews of Modern Physics 65 (2) 499 (1993)
https://doi.org/10.1103/RevModPhys.65.499
Mean-field theory for the Q-state Potts-glass neural network with biased patterns
D Bolle, R Cools, P Dupont and J HuyghebaertJournal of Physics A: Mathematical and General 26 (3) 549 (1993)
https://doi.org/10.1088/0305-4470/26/3/017
Basin of attraction in networks of multistate neurons
M. Bouten and A. EngelPhysical Review E 47 (2) 1397 (1993)
https://doi.org/10.1103/PhysRevE.47.1397
On the Q-state neuron problem in attractor neural networks
G.A. KohringNeural Networks 6 (4) 573 (1993)
https://doi.org/10.1016/S0893-6080(05)80060-7
Multistate perceptrons: learning rule and perceptron of maximal stability
E Elizalde and S GomezJournal of Physics A: Mathematical and General 25 (19) 5039 (1992)
https://doi.org/10.1088/0305-4470/25/19/016
Learning withQ-state clock neurons
F. Gerl, Karin Bauer and U. KreyZeitschrift f�r Physik B Condensed Matter 88 (3) 339 (1992)
https://doi.org/10.1007/BF01470923
Memorizing polymers' shapes and permutations
V S Dotsenko, S Franz and M MezardJournal of Physics A: Mathematical and General 25 (24) 6631 (1992)
https://doi.org/10.1088/0305-4470/25/24/017
Invariant recognition in Potts glass neural networks
H Vogt and A ZippeliusJournal of Physics A: Mathematical and General 25 (8) 2209 (1992)
https://doi.org/10.1088/0305-4470/25/8/032
Thermodynamic properties of theQ-state Potts-glass neural network
D. Bollé, P. Dupont and J. HuyghebaertPhysical Review A 45 (6) 4194 (1992)
https://doi.org/10.1103/PhysRevA.45.4194
Properties of neural networks storing spatially correlated patterns
R MonassonJournal of Physics A: Mathematical and General 25 (13) 3701 (1992)
https://doi.org/10.1088/0305-4470/25/13/019