Jeffrey A. Jargon, Ph.D.

Affiliations: 
2003 University of Colorado, Boulder, Boulder, CO, United States 
Area:
Electronics and Electrical Engineering
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"Jeffrey Jargon"

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Donald C. DeGroot grad student 2003 CU Boulder
 (Measurement -based modeling of vector network analyzer calibration standards and nonlinear microwave devices using artificial neural networks.)
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Publications

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Gu D, Jargon JA, Ryan MJ, et al. (2020) Influence of Noise on Scattering-Parameter Measurements Ieee Transactions On Microwave Theory and Techniques. 1-1
Manurkar P, Horansky RD, Jamroz BF, et al. (2020) Precision Millimeter-Wave-Modulated Wideband Source at 92.4 GHz as a Step Toward an Over-the-Air Reference Ieee Transactions On Microwave Theory and Techniques. 68: 2644-2654
Jargon JA, Williams DF, Sanders A. (2018) The Relationship Between Switch-Term-Corrected Scattering-Parameters and Wave-Parameters Measured With a Two-Port Vector Network Analyzer Ieee Microwave and Wireless Components Letters. 28: 951-953
Remley KA, Gordon JA, Novotny D, et al. (2017) Measurement Challenges for 5G and Beyond: An Update from the National Institute of Standards and Technology Ieee Microwave Magazine. 18: 41-56
Cho C, Lee JG, Hale PD, et al. (2016) Calibration of Time-Interleaved Errors in Digital Real-Time Oscilloscopes Ieee Transactions On Microwave Theory and Techniques
Avolio G, Raffo A, Jargon J, et al. (2015) Evaluation of Uncertainty in Temporal Waveforms of Microwave Transistors Ieee Transactions On Microwave Theory and Techniques. 63: 2353-2363
Remley KA, Williams DF, Hale PD, et al. (2015) Millimeter-Wave Modulated-Signal and Error-Vector-Magnitude Measurement With Uncertainty Ieee Transactions On Microwave Theory and Techniques. 63: 1710-1720
Wu X, Jargon JA, Paraschis L, et al. (2011) ANN-Based Optical Performance Monitoring of QPSK Signals Using Parameters Derived From Balanced-Detected Asynchronous Diagrams Ieee Photonics Technology Letters. 23: 248-250
Jargon JA, Wu X, Choi HY, et al. (2010) Optical performance monitoring of QPSK data channels by use of neural networks trained with parameters derived from asynchronous constellation diagrams. Optics Express. 18: 4931-8
Jargon JA, Wu X, Willner AE. (2009) Optical Performance Monitoring Using Artificial Neural Networks Trained With Eye-Diagram Parameters Ieee Photonics Technology Letters. 21: 54-56
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