Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Yuan-qin Wang"'
Publikováno v:
Journal of Huazhong University of Science and Technology [Medical Sciences]. 34:114-119
Recent studies have shown that Er-Zhi-Wan (EZW), a traditional Chinese medicine consisting of Herba Ecliptae (HE) and Fructus Ligustri Lucidi (FLL), had a definite antiosteoporotic effect on osteoporotic femur, but its effect on osteoporosis of alveo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6ec9352c161682ee4bb7c797ddb03e4b
https://doi.org/10.1007/s11596-014-1241-0
https://doi.org/10.1007/s11596-014-1241-0
This book describes grouping detection and initiation; group initiation algorithm based on geometry center; data association and track continuity; as well as separate-detection and situation cognition for group-target. It specifies the tracking of th
Publikováno v:
Group-target Tracking
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cf6b398fc742ec5143437639dd27750a
https://doi.org/10.1007/978-981-10-1888-6
https://doi.org/10.1007/978-981-10-1888-6
Publikováno v:
Group-target Tracking ISBN: 9789811018862
Purely from the perspective of target tracking, we have completed the pretreatment of group-target measurement, group-target track initiation, single group-target data correlating and track maintenance, and multi-group-target data correlating and tra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e6bb01cc877251736cc15e4554f55dc3
https://doi.org/10.1007/978-981-10-1888-6_6
https://doi.org/10.1007/978-981-10-1888-6_6
Publikováno v:
Group-target Tracking ISBN: 9789811018862
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b485b9c516b990bbdd6dac15a62e9fff
https://doi.org/10.1007/978-981-10-1888-6_1
https://doi.org/10.1007/978-981-10-1888-6_1
Publikováno v:
Group-target Tracking ISBN: 9789811018862
Multi-targets tracking data association can generate three areas: correctly correlated area, unstable correlated area, and mistaken correlated area. Any radar cannot choose its tracking environment and target distance, but can enhance scan frequency
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0cdcd9cfae07c44e7a11aacb211848ea
https://doi.org/10.1007/978-981-10-1888-6_3
https://doi.org/10.1007/978-981-10-1888-6_3
Publikováno v:
Group-target Tracking ISBN: 9789811018862
Multi-target tracking data association is a difficulty and also a key problem to be solved firstly in multi-target tracking. When tracking single target under situation of returns in density, the continuous occurrence of the measurement from near tar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a21f4dbca362a56d86be78780b13ce93
https://doi.org/10.1007/978-981-10-1888-6_5
https://doi.org/10.1007/978-981-10-1888-6_5
Publikováno v:
Group-target Tracking ISBN: 9789811018862
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::382d6b8027293f7ee37bb2ce1a7d69bd
https://doi.org/10.1007/978-981-10-1888-6_2
https://doi.org/10.1007/978-981-10-1888-6_2
Publikováno v:
Group-target Tracking ISBN: 9789811018862
As we know, the nearest-neighboring algorithm and probability association algorithm in Bayesian algorithm are very successful two data association algorithms. The nearest-neighboring method, as one of the comparatively effective data association meth
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::65da7d52f4ca31f39a3155133ef55007
https://doi.org/10.1007/978-981-10-1888-6_4
https://doi.org/10.1007/978-981-10-1888-6_4
Publikováno v:
Advanced Materials Research. 462:10-16
A particle filtering equalization algorithm with unknown noise variance is presented based on the optical particle sampling using the optical importance function. The optical importance function with unknown noise variance is deduced by analytically
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8290df1c06bc5f0eb91077dd79e182d8
https://doi.org/10.4028/www.scientific.net/amr.462.10
https://doi.org/10.4028/www.scientific.net/amr.462.10