Publication: Breakpoint distance los path loss model for indoor communication using anfis
dc.contributor.author | Supachai Phaiboon | en_US |
dc.contributor.author | Pisit Phokharatkul | en_US |
dc.contributor.author | Suripon Somkurnpanich | en_US |
dc.contributor.other | Mahidol University | en_US |
dc.contributor.other | King Mongkut's Institute of Technology Ladkrabang | en_US |
dc.date.accessioned | 2018-06-21T08:13:39Z | |
dc.date.available | 2018-06-21T08:13:39Z | |
dc.date.issued | 2005-12-01 | en_US |
dc.description.abstract | Breakpoint distance LOS model for indoor wireless communication is presented in this paper. The model is based on the determination of the breakpoint distance and % of wall area between the transmitter and the receiver. The propagation path losses are predicted with adaptive neuro - fuzzy inference systems (ANFIS), trained with measurements at the frequency of 1.8 GHz. The advantage of the ANFIS with hybrid least squares and gradient descent algorithms is fast convergence compared with original neural network. Comparison of our predicted results to measurements indicate that improvements in accuracy over conventional empirical models are achieved. | en_US |
dc.identifier.citation | Proceedings of the Second IASTED International Multi-Conference on Automation, Control, and Information Technology - Communication Systems. Vol.2005, (2005), 45-50 | en_US |
dc.identifier.other | 2-s2.0-33751260807 | en_US |
dc.identifier.uri | https://repository.li.mahidol.ac.th/handle/20.500.14594/16499 | |
dc.rights | Mahidol University | en_US |
dc.rights.holder | SCOPUS | en_US |
dc.source.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=33751260807&origin=inward | en_US |
dc.subject | Engineering | en_US |
dc.title | Breakpoint distance los path loss model for indoor communication using anfis | en_US |
dc.type | Conference Paper | en_US |
dspace.entity.type | Publication | |
mu.datasource.scopus | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=33751260807&origin=inward | en_US |