Matches in SemOpenAlex for { <https://semopenalex.org/work/W2108597974> ?p ?o ?g. }
- W2108597974 endingPage "6316" @default.
- W2108597974 startingPage "6297" @default.
- W2108597974 abstract "Distributed estimation of Gaussian mixtures has many applications in wireless sensor network (WSN), and its energy-efficient solution is still challenging. This paper presents a novel diffusion-based EM algorithm for this problem. A diffusion strategy is introduced for acquiring the global statistics in EM algorithm in which each sensor node only needs to communicate its local statistics to its neighboring nodes at each iteration. This improves the existing consensus-based distributed EM algorithm which may need much more communication overhead for consensus, especially in large scale networks. The robustness and scalability of the proposed approach can be achieved by distributed processing in the networks. In addition, we show that the proposed approach can be considered as a stochastic approximation method to find the maximum likelihood estimation for Gaussian mixtures. Simulation results show the efficiency of this approach." @default.
- W2108597974 created "2016-06-24" @default.
- W2108597974 creator A5025288570 @default.
- W2108597974 creator A5029817092 @default.
- W2108597974 creator A5078773537 @default.
- W2108597974 date "2011-06-14" @default.
- W2108597974 modified "2023-10-14" @default.
- W2108597974 title "Diffusion-Based EM Algorithm for Distributed Estimation of Gaussian Mixtures in Wireless Sensor Networks" @default.
- W2108597974 cites W1963998540 @default.
- W2108597974 cites W1985690171 @default.
- W2108597974 cites W1994616650 @default.
- W2108597974 cites W2093356327 @default.
- W2108597974 cites W2097380742 @default.
- W2108597974 cites W2100169223 @default.
- W2108597974 cites W2104064843 @default.
- W2108597974 cites W2104924323 @default.
- W2108597974 cites W2107396783 @default.
- W2108597974 cites W2110482969 @default.
- W2108597974 cites W2114557042 @default.
- W2108597974 cites W2118776392 @default.
- W2108597974 cites W2119072456 @default.
- W2108597974 cites W2119102657 @default.
- W2108597974 cites W2119434824 @default.
- W2108597974 cites W2121820607 @default.
- W2108597974 cites W2122304153 @default.
- W2108597974 cites W2130359405 @default.
- W2108597974 cites W2130442323 @default.
- W2108597974 cites W2141788746 @default.
- W2108597974 cites W2143667229 @default.
- W2108597974 cites W2158307424 @default.
- W2108597974 cites W2168452204 @default.
- W2108597974 cites W2169329579 @default.
- W2108597974 doi "https://doi.org/10.3390/s110606297" @default.
- W2108597974 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/3231413" @default.
- W2108597974 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/22163956" @default.
- W2108597974 hasPublicationYear "2011" @default.
- W2108597974 type Work @default.
- W2108597974 sameAs 2108597974 @default.
- W2108597974 citedByCount "33" @default.
- W2108597974 countsByYear W21085979742012 @default.
- W2108597974 countsByYear W21085979742013 @default.
- W2108597974 countsByYear W21085979742014 @default.
- W2108597974 countsByYear W21085979742015 @default.
- W2108597974 countsByYear W21085979742016 @default.
- W2108597974 countsByYear W21085979742017 @default.
- W2108597974 countsByYear W21085979742018 @default.
- W2108597974 countsByYear W21085979742019 @default.
- W2108597974 countsByYear W21085979742020 @default.
- W2108597974 countsByYear W21085979742021 @default.
- W2108597974 crossrefType "journal-article" @default.
- W2108597974 hasAuthorship W2108597974A5025288570 @default.
- W2108597974 hasAuthorship W2108597974A5029817092 @default.
- W2108597974 hasAuthorship W2108597974A5078773537 @default.
- W2108597974 hasBestOaLocation W21085979741 @default.
- W2108597974 hasConcept C10000559 @default.
- W2108597974 hasConcept C104317684 @default.
- W2108597974 hasConcept C108037233 @default.
- W2108597974 hasConcept C111919701 @default.
- W2108597974 hasConcept C11413529 @default.
- W2108597974 hasConcept C120314980 @default.
- W2108597974 hasConcept C121332964 @default.
- W2108597974 hasConcept C130120984 @default.
- W2108597974 hasConcept C163716315 @default.
- W2108597974 hasConcept C185592680 @default.
- W2108597974 hasConcept C24590314 @default.
- W2108597974 hasConcept C2779960059 @default.
- W2108597974 hasConcept C31258907 @default.
- W2108597974 hasConcept C41008148 @default.
- W2108597974 hasConcept C41971633 @default.
- W2108597974 hasConcept C48044578 @default.
- W2108597974 hasConcept C55493867 @default.
- W2108597974 hasConcept C555944384 @default.
- W2108597974 hasConcept C62520636 @default.
- W2108597974 hasConcept C63479239 @default.
- W2108597974 hasConcept C76155785 @default.
- W2108597974 hasConcept C77088390 @default.
- W2108597974 hasConceptScore W2108597974C10000559 @default.
- W2108597974 hasConceptScore W2108597974C104317684 @default.
- W2108597974 hasConceptScore W2108597974C108037233 @default.
- W2108597974 hasConceptScore W2108597974C111919701 @default.
- W2108597974 hasConceptScore W2108597974C11413529 @default.
- W2108597974 hasConceptScore W2108597974C120314980 @default.
- W2108597974 hasConceptScore W2108597974C121332964 @default.
- W2108597974 hasConceptScore W2108597974C130120984 @default.
- W2108597974 hasConceptScore W2108597974C163716315 @default.
- W2108597974 hasConceptScore W2108597974C185592680 @default.
- W2108597974 hasConceptScore W2108597974C24590314 @default.
- W2108597974 hasConceptScore W2108597974C2779960059 @default.
- W2108597974 hasConceptScore W2108597974C31258907 @default.
- W2108597974 hasConceptScore W2108597974C41008148 @default.
- W2108597974 hasConceptScore W2108597974C41971633 @default.
- W2108597974 hasConceptScore W2108597974C48044578 @default.
- W2108597974 hasConceptScore W2108597974C55493867 @default.
- W2108597974 hasConceptScore W2108597974C555944384 @default.
- W2108597974 hasConceptScore W2108597974C62520636 @default.
- W2108597974 hasConceptScore W2108597974C63479239 @default.
- W2108597974 hasConceptScore W2108597974C76155785 @default.
- W2108597974 hasConceptScore W2108597974C77088390 @default.