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Jun Fan

Researcher at Missouri University of Science and Technology

Publications -  505
Citations -  7033

Jun Fan is an academic researcher from Missouri University of Science and Technology. The author has contributed to research in topics: Printed circuit board & Equivalent circuit. The author has an hindex of 36, co-authored 482 publications receiving 5641 citations. Previous affiliations of Jun Fan include Ulsan National Institute of Science and Technology & University of Missouri.

Papers
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Proceedings ArticleDOI

Early Time Charge Replenishment of the Power Delivery Network in Multi-Layer PCBs

TL;DR: In this article, the authors investigated the depletion of charges stored between the power bus in the time domain as a function of the plane thickness, SMT decoupling closeness and interconnect inductance values.
Proceedings ArticleDOI

Capacitance calculation of TSVs using an integral equation method based on partial capacitances

TL;DR: In this article, an integral equation method based on partial capacitances is used to extract the capacitance between two through-silicon-vias (TSVs), and the results are validated by comparing the extracted capacitance with commercial software based on the finite element method.

A Novel Machine-Learning-Based Batch Selection Method in Sparse Near-Field Scanning

Abstract: This article presents a novel and efficient batch data selection method based on active and unsupervised learning in real-time near-field scanning. The new approach shows a remarkable advantage over random sampling in reducing the number of scanning data samples and the total scanning time. Moreover, careful hyperparameter tuning is unnecessary, as the performance is insensitive to the hyperparameter values. After randomly selecting some initial points, three key steps are sequentially and iteratively implemented. First, the query-by-committee (QBC) method is adopted to evaluate the uncertainties of the unobserved positions using different interpolation functions and select an “uncertain” group with the largest variances. Second, the weighted K-means clustering (WKMC) method divides the “uncertain” group into multiple clusters and selects the representative samples by choosing the most uncertain point in each cluster to ensure diversity. Finally, an estimated variance change (EVC) method is proposed to select the most representative samples to enhance diversity further. The proposed approach of this article, referred to as the QWE (QBC + WKMC + EVC) method, can well balance uncertainty and diversity with high efficiency. The newly proposed QWE approach is validated in both simulations and measurements of near-field scanning. The batch data selection method of this article can be extended to other multidimensional regression modeling problems in which data acquisition is expensive.
Proceedings ArticleDOI

The effects of reference capacitors on signal transmission through single-ended traces in multi-layer PCBs

TL;DR: In this paper, the effects of the number and locations of reference capacitors on signal transmission are studied, and reported in the frequency ranges where the increased losses occur are ranges containing board distributed resonance frequencies.