Vignesh Rajamani
Oklahoma State University–Stillwater
35 Papers
97 Citations
Vignesh Rajamani is an academic researcher from Oklahoma State University–Stillwater. The author has contributed to research in topics: Electromagnetic reverberation chamber & Electromagnetic compatibility. The author has an hindex of 7, co-authored 32 publications.
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Papers
Validation of modal/MoM in shielding effectiveness studies of rectangular enclosures with apertures
TL;DR: In this article, the authors discussed the validation of Modal/method of moments (MoM) including cases when the apertures are made as big as the wall of the enclosure (equivalent to having one side of the cavity open).
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Stirred-Mode Operation of Reverberation Chambers for EMC Testing
TL;DR: An experimental investigation shows that the spectral information available within the chamber is the same for both the stepped and the stirred operation and is independent of the tuner speed provided that the chamber transient time is small compared to the rate at which the fields change inside the chamber due to the Tuner rotation.
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A New ANN-Based Modeling Approach for Rapid EMI/EMC Analysis of PCB and Shielding Enclosures
TL;DR: A new artificial neural networks-based reverse-modeling approach for efficient electromagnetic compatibility (EMC) analysis of printed circuit boards (PCBs) and shielding enclosures that improves the accuracy of conventional or standard neural models by reversing the input-output variables in a systematic manner.
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Validation of modal/MoM in shielding effectiveness studies of rectangular enclosures with apertures
Vignesh Rajamani,Charles F. Bunting +1 more
- 03 Oct 2005
TL;DR: In this article, the authors discussed the validation of modal/MoM including cases for when the apertures are made as big as the wall of the enclosure (equivalent to having one side of the cavity open).
32
Introduction to feature selective validation (FSV)
Vignesh Rajamani,Charles F. Bunting,Antonio Orlandi,Alistair Duffy +3 more
- 09 Jul 2006
TL;DR: The feature selective validation tool is a standalone application that implements the FSV method originally developed by Dr Anthony Martin, and allows automated comparisons of large volumes of complex data whilst reliably categorising the results into a common set of quality bands.
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