6533b839fe1ef96bd12a6ee2
RESEARCH PRODUCT
Multitasking associative networks.
Elena AgliariElena AgliariFrancesco MoauroFrancesco GuerraFrancesco GuerraAndrea GalluzziAdriano Barrasubject
NeuronsRestricted Boltzmann machineTheoretical computer scienceArtificial neural networkComputer scienceMonte Carlo methodComplex systemGeneral Physics and AstronomyFOS: Physical sciencesStatistical mechanicsDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksPhysics and Astronomy (all)Human multitaskingNeural Networks ComputerNerve NetEquivalence (measure theory)Associative propertydescription
We introduce a bipartite, diluted and frustrated, network as a sparse restricted Boltzman machine and we show its thermodynamical equivalence to an associative working memory able to retrieve multiple patterns in parallel without falling into spurious states typical of classical neural networks. We focus on systems processing in parallel a finite (up to logarithmic growth in the volume) amount of patterns, mirroring the low-level storage of standard Amit-Gutfreund-Sompolinsky theory. Results obtained trough statistical mechanics, signal-to-noise technique and Monte Carlo simulations are overall in perfect agreement and carry interesting biological insights. Indeed, these associative networks pave new perspectives in the understanding of multitasking features expressed by complex systems, e.g. neural and immune networks.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2012-01-01 | Physical review letters |