Matches in SemOpenAlex for { <https://semopenalex.org/work/W2039124457> ?p ?o ?g. }
Showing items 1 to 93 of
93
with 100 items per page.
- W2039124457 endingPage "321" @default.
- W2039124457 startingPage "301" @default.
- W2039124457 abstract "This paper presents two simple optimization techniques based on combining the Langevin Equation with the Hopfield Model. Proposed models – referred as stochastic model (SM) and pulsed noise model (PNM) – can be regarded as straightforward stochastic extensions of the Hopfield optimization network. Both models follow the idea of stochastic neural network (Levy and Adams, IEEE Conference on Neural Networks, vol. III, San Diego, USA, 1987, pp. 681–689) and diffusion machine (Wong, Algorithmica 6 (1991) 466–478). They differ form the referred approaches by the nature of noises and the way of their injection. Optimization with stochastic model, unlike in the previous works, in which δ-correlated Gaussian noises were considered, is based on Gaussian noises with positive autocorrelation times. This is a reasonable assumption from a hardware implementation point of view. In the other model – pulsed noise model, Gaussian noises are injected to the system only at certain time instances, as opposed to continuously maintained δ-correlated noises used in the previous related works. In both models (SM and PNM) intensities of injected noises are independent of neurons’ potentials. Moreover, instead of impractically long inverse logarithmic cooling schedules, the linear cooling is tested. With the above strong simplifications neither SM nor PNM is expected to rigorously maintain thermal equilibrium (TE). However, numerical tests based on the canonical Gibbs–Boltzmann distribution show, that differences between rigorous and estimated values of TE parameters are relatively low (within a few percent). In this sense both models are said to perform quasithermal equilibrium. Optimization performance and quasithermal equilibrium properties of both models are presented based on the travelling salesman problem (TSP)." @default.
- W2039124457 created "2016-06-24" @default.
- W2039124457 creator A5073814691 @default.
- W2039124457 date "2000-01-01" @default.
- W2039124457 modified "2023-10-16" @default.
- W2039124457 title "Optimization with the Hopfield network based on correlated noises: Experimental approach" @default.
- W2039124457 cites W1597286183 @default.
- W2039124457 cites W1823123077 @default.
- W2039124457 cites W1995341919 @default.
- W2039124457 cites W2013158126 @default.
- W2039124457 cites W2024060531 @default.
- W2039124457 cites W2041898787 @default.
- W2039124457 cites W2042492924 @default.
- W2039124457 cites W2047620565 @default.
- W2039124457 cites W2050203848 @default.
- W2039124457 cites W2053887662 @default.
- W2039124457 cites W2069559839 @default.
- W2039124457 cites W2076998221 @default.
- W2039124457 cites W2081439556 @default.
- W2039124457 cites W2091230209 @default.
- W2039124457 cites W2112246162 @default.
- W2039124457 cites W2114967060 @default.
- W2039124457 cites W2121890596 @default.
- W2039124457 cites W2128084896 @default.
- W2039124457 cites W2147881255 @default.
- W2039124457 doi "https://doi.org/10.1016/s0925-2312(99)00132-0" @default.
- W2039124457 hasPublicationYear "2000" @default.
- W2039124457 type Work @default.
- W2039124457 sameAs 2039124457 @default.
- W2039124457 citedByCount "7" @default.
- W2039124457 countsByYear W20391244572012 @default.
- W2039124457 countsByYear W20391244572022 @default.
- W2039124457 crossrefType "journal-article" @default.
- W2039124457 hasAuthorship W2039124457A5073814691 @default.
- W2039124457 hasConcept C105795698 @default.
- W2039124457 hasConcept C11413529 @default.
- W2039124457 hasConcept C115961682 @default.
- W2039124457 hasConcept C121332964 @default.
- W2039124457 hasConcept C121864883 @default.
- W2039124457 hasConcept C126255220 @default.
- W2039124457 hasConcept C154945302 @default.
- W2039124457 hasConcept C163716315 @default.
- W2039124457 hasConcept C192576344 @default.
- W2039124457 hasConcept C2777577648 @default.
- W2039124457 hasConcept C28826006 @default.
- W2039124457 hasConcept C33923547 @default.
- W2039124457 hasConcept C41008148 @default.
- W2039124457 hasConcept C4199805 @default.
- W2039124457 hasConcept C46421273 @default.
- W2039124457 hasConcept C50644808 @default.
- W2039124457 hasConcept C5297727 @default.
- W2039124457 hasConcept C62520636 @default.
- W2039124457 hasConcept C99498987 @default.
- W2039124457 hasConceptScore W2039124457C105795698 @default.
- W2039124457 hasConceptScore W2039124457C11413529 @default.
- W2039124457 hasConceptScore W2039124457C115961682 @default.
- W2039124457 hasConceptScore W2039124457C121332964 @default.
- W2039124457 hasConceptScore W2039124457C121864883 @default.
- W2039124457 hasConceptScore W2039124457C126255220 @default.
- W2039124457 hasConceptScore W2039124457C154945302 @default.
- W2039124457 hasConceptScore W2039124457C163716315 @default.
- W2039124457 hasConceptScore W2039124457C192576344 @default.
- W2039124457 hasConceptScore W2039124457C2777577648 @default.
- W2039124457 hasConceptScore W2039124457C28826006 @default.
- W2039124457 hasConceptScore W2039124457C33923547 @default.
- W2039124457 hasConceptScore W2039124457C41008148 @default.
- W2039124457 hasConceptScore W2039124457C4199805 @default.
- W2039124457 hasConceptScore W2039124457C46421273 @default.
- W2039124457 hasConceptScore W2039124457C50644808 @default.
- W2039124457 hasConceptScore W2039124457C5297727 @default.
- W2039124457 hasConceptScore W2039124457C62520636 @default.
- W2039124457 hasConceptScore W2039124457C99498987 @default.
- W2039124457 hasIssue "1-4" @default.
- W2039124457 hasLocation W20391244571 @default.
- W2039124457 hasOpenAccess W2039124457 @default.
- W2039124457 hasPrimaryLocation W20391244571 @default.
- W2039124457 hasRelatedWork W1538052603 @default.
- W2039124457 hasRelatedWork W1976760191 @default.
- W2039124457 hasRelatedWork W2012039318 @default.
- W2039124457 hasRelatedWork W2038467384 @default.
- W2039124457 hasRelatedWork W2049417036 @default.
- W2039124457 hasRelatedWork W2078053261 @default.
- W2039124457 hasRelatedWork W2085780643 @default.
- W2039124457 hasRelatedWork W2926619812 @default.
- W2039124457 hasRelatedWork W3103504659 @default.
- W2039124457 hasRelatedWork W3187194562 @default.
- W2039124457 hasVolume "30" @default.
- W2039124457 isParatext "false" @default.
- W2039124457 isRetracted "false" @default.
- W2039124457 magId "2039124457" @default.
- W2039124457 workType "article" @default.