scholarly journals Automated frequency and quality‐factor matching method for frequency modulated / rate integrating gyroscope

2019 ◽  
Vol 209 (3-4) ◽  
pp. 57-63
Author(s):  
Takashiro Tsukamoto ◽  
Shuji Tanaka
Keyword(s):  
Quality Factor ◽  
Matching Method ◽  
Factor Matching

Automated Frequency and Quality-Factor Matching Method for Frequency Modulated / Rate Integrating Gyroscope

2019 ◽  
Vol 139 (8) ◽  
pp. 219-224
Author(s):  
Takashiro Tsukamoto ◽  
Shuji Tanaka
Keyword(s):  
Quality Factor ◽  
Matching Method ◽  
Factor Matching

Enhancing selectivity of infrared emitters through quality-factor matching

2015 ◽  
Author(s):  
Enas Sakr ◽  
Zhiguang Zhou ◽  
Peter Bermel
Keyword(s):  
Quality Factor ◽  
Infrared Emitters ◽  
Factor Matching

scholarly journals Multiscale Spatial Polygonal Object Granularity Factor Matching Method Based on BPNN

2021 ◽  
Vol 10 (2) ◽  
pp. 75
Author(s):  
Daoye Zhu ◽  
Chengqi Cheng ◽  
Weixin Zhai ◽  
Yihang Li ◽  
Shizhong Li ◽  
...  
Keyword(s):  
Spatial Data ◽  
Evaluation Index ◽  
Backpropagation Neural Network ◽  
Matching Method ◽  
Matching Model ◽  
Object Matching ◽  
Recognition Ability ◽  
Factor Evaluation ◽  
Matching Score ◽  
Factor Matching

Spatial object matching is one of the fundamental technologies used for updating and merging spatial data. This study focused mainly on the matching optimization of multiscale spatial polygonal objects. We proposed a granularity factor evaluation index that was developed to promote the recognition ability of complex matches in multiscale spatial polygonal object matching. Moreover, we designed the granularity factor matching model based on a backpropagation neural network (BPNN) and designed a multistage matching workflow. Our approach was validated experimentally using two topographical datasets at two different scales: 1:2000 and 1:10,000. Our results indicate that the granularity factor is effective both in improving the matching score of complex matching and reducing the occurrence of missing matching, and our matching model is suitable for multiscale spatial polygonal object matching, with a high precision and recall reach of 97.2% and 90.6%.

GREEN'S FUNCTION MATCHING METHOD FOR REALISTIC CALCULATIONS OF INTERFACES

1985 ◽  
Vol 46 (C4) ◽  
pp. C4-321-C4-329 ◽  
Author(s):  
E. Molinari ◽  
G. B. Bachelet ◽  
M. Altarelli
Keyword(s):  
Green’S Function ◽  
Green's Function ◽  
Matching Method

NÉEL LINES STRUCTURES IN UNIAXIAL FERROMAGNETS WITH QUALITY FACTOR Q > 1

1988 ◽  
Vol 49 (C8) ◽  
pp. C8-1947-C8-1948
Author(s):  
J. Miltat ◽  
P. Trouilloud
Keyword(s):  
Quality Factor ◽  
Quality Factor Q

385. A Paired Concentration Matching Method for Stationary Gas Monitor Evaluation

1999 ◽  
Author(s):  
S. Yan ◽  
S. Wong ◽  
J. Yu
Keyword(s):  
Matching Method

The INFLUENCE OF surface roughness of aluminum films on quality factor of microelectronic BAW-resonator

2018 ◽  
pp. 112-120
Author(s):  
V. N. Zima ◽  
◽  
T. N. Torgash ◽  
A. G. Kozlov ◽  
◽  
...  
Keyword(s):  
Surface Roughness ◽  
Quality Factor ◽  
Aluminum Films

Error Prediction of the Point Matching Method for EM Scattering from a Conducting Rectangular Cylinder

2009 ◽  
Vol 129 (10) ◽  
pp. 727-728 ◽  
Author(s):  
Shinichiro Ohnuki ◽  
Takahisa Mochizuki ◽  
Tsuneki Yamasaki
Keyword(s):  
Error Prediction ◽  
Matching Method ◽  
Em Scattering ◽  
Point Matching ◽  
Rectangular Cylinder
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