Background Receiver IQ Imbalance Correction for in-Field and Post-Production Testing and Calibration

2021 ◽  
Author(s):  
Muslum Emir Avci ◽  
Sule Ozev
Keyword(s):  
Production Testing ◽  
Iq Imbalance ◽  
Post Production

scholarly journals Stabilization of vibro-thermal processes during post-production testing of rolling bearings

Diagnostyka ◽  
2019 ◽  
Vol 20 (3) ◽  
pp. 53-62 ◽  
Author(s):  
Bartosz Jakubek ◽  
Roman Barczewski ◽  
Wojciech Rukat ◽  
Leszek Rozanski ◽  
Mateusz Wrobel
Keyword(s):  
Thermal Processes ◽  
Production Testing ◽  
Rolling Bearings ◽  
Post Production

Discussion on “Production testing equipment” at the Birmingham Section of the Institution

1932 ◽  
Vol 11 (1) ◽  
pp. 46
Author(s):  
R.H. Youngash ◽  
E.W. Field ◽  
I.H. Wright ◽  
J.H. Garnett ◽  
H.C. Armitage ◽  
...  
Keyword(s):  
Testing Equipment ◽  
Production Testing

Digital Compensation of IQ Imbalance for Dual-Carrier Double Conversion Receivers

2012 ◽  
Vol E95.B (5) ◽  
pp. 1612-1619 ◽  
Author(s):  
Chester Sungchung PARK ◽  
Fitzgerald Sungkyung PARK
Keyword(s):  
Digital Compensation ◽  
Iq Imbalance

scholarly journals Inspection of Transparent Objects with Varying Light Scattering Using a Frangi Filter

2021 ◽  
Vol 7 (2) ◽  
pp. 27
Author(s):  
Dieter P. Gruber ◽  
Matthias Haselmann
Keyword(s):  
Light Scattering ◽  
Machine Vision ◽  
Nearest Neighbor ◽  
Production Testing ◽  
Transparent Objects ◽  
Frangi Filter ◽  
Anomaly Score ◽  
Difference Images ◽  
New Machine

This paper proposes a new machine vision method to test the quality of a semi-transparent automotive illuminant component. Difference images of Frangi filtered surface images are used to enhance defect-like image structures. In order to distinguish allowed structures from defective structures, morphological features are extracted and used for a nearest-neighbor-based anomaly score. In this way, it could be demonstrated that a segmentation of occurring defects is possible on transparent illuminant parts. The method turned out to be fast and accurate and is therefore also suited for in-production testing.

Chemical composition determines the bioenergy potential of food waste from pre- and post-production

2021 ◽  
Author(s):  
Beatriz Salustiano Pereira ◽  
Raíssa Nobre Castrisana ◽  
Caroline de Freitas ◽  
Jonas Contiero ◽  
Michel Brienzo
Keyword(s):  
Chemical Composition ◽  
Food Waste ◽  
Post Production
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