Zobrazeno 1 - 10
of 15
pro vyhledávání: '"G. M. Shim"'
Publikováno v:
Journal of Statistical Physics. 91:125-153
Using a probabilistic approach, the parallel dynamics of fully connected Q-Ising neural networks is studied for arbitrary Q. A novel recursive scheme is set up to determine the time evolution of the order parameters through the evolution of the distr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::94b85273ffe071ccb78d1aff9d78c183
https://doi.org/10.1023/a:1023088004195
https://doi.org/10.1023/a:1023088004195
Publikováno v:
International Journal of Neural Systems. :655-664
Using a signal-to-noise analysis, the effects of nonlinear modulation of the Hebbian learning rule in the multi-class proximity problem are investigated. Both random classification and classification provided by a Gaussian and a binary teacher are tr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b064350316c82e87a7b143f9f8be75ce
https://doi.org/10.1142/s0129065796000634
https://doi.org/10.1142/s0129065796000634
Publikováno v:
Journal of Physics A: Mathematical and General. 26:3697-3705
The authors investigate the effects of the synaptic noise in neural networks at finite temperatures. The analytic results are obtained through the use of the path-integral formulation which facilitates performing the quenched average over the random
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2ff620d6a1cac6aea006e7c7fa414c88
https://doi.org/10.1088/0305-4470/26/15/019
https://doi.org/10.1088/0305-4470/26/15/019
Publikováno v:
Physical Review A. 45:1238-1248
The layered feedforward neural network is extended to a q-state Potts-glass model. The Potts-glass version of the network is realized by imposing local inhibition on a group of Ising spins and introducing competitive updating rules on them. The dynam
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d107addd0858f0d51239baaa8b43403f
https://doi.org/10.1103/physreva.45.1238
https://doi.org/10.1103/physreva.45.1238
Publikováno v:
Physical Review A. 43:7012-7018
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a9b2b08e7a5a41b5a1313fdfefd62887
https://doi.org/10.1103/physreva.43.7012
https://doi.org/10.1103/physreva.43.7012
Publikováno v:
Physical Review A. 43:1079-1089
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::27bf594089a4d54c3d3519752b56c952
https://doi.org/10.1103/physreva.43.1079
https://doi.org/10.1103/physreva.43.1079
Publikováno v:
Physical Review Letters. 94
We study a zero range process on scale-free networks in order to investigate how network structure influences particle dynamics. The zero range process is defined with the particle jumping rate function $p(n)=n^\delta$. We show analytically that a co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::92a512ca153dc02a3a3167df4287a13c
https://doi.org/10.1103/physrevlett.94.198701
https://doi.org/10.1103/physrevlett.94.198701
Publikováno v:
Physical review. E, Statistical, nonlinear, and soft matter physics. 70(3 Pt 1)
We present an analytic study of the three-urn model for separation of sand. We solve analytically the master equation and the first-passage problem. We find that the stationary probability distribution obeys the detailed balance and is governed by th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::04106f35ad6b9a31db7f3e25603e657c
https://pubmed.ncbi.nlm.nih.gov/15524519
https://pubmed.ncbi.nlm.nih.gov/15524519
Publikováno v:
Scopus-Elsevier
We present an analytic study of the urn model for separation of sand recently introduced by Lipowski and Droz (Phys. Rev. E 65, 031307 (2002)). We solve analytically the master equation and the first-passage problem. The analytic results confirm the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::19ca2fd5e85bb3458416e3ff7892844a
https://pubmed.ncbi.nlm.nih.gov/12636492
https://pubmed.ncbi.nlm.nih.gov/12636492
Autor:
Désiré Bollé, G. M. Shim
Publikováno v:
Physical review. E, Statistical, nonlinear, and soft matter physics. 65(6 Pt 2)
The time evolution of the local field in symmetric Q-Ising neural networks is studied for arbitrary Q. In particular, the structure of the noise and the appearance of gaps in the probability distribution are discussed. Results are presented for sever
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::906e29e6e3abd7c8008ad644f81f213a
https://pubmed.ncbi.nlm.nih.gov/12188867
https://pubmed.ncbi.nlm.nih.gov/12188867