Qingxun Wang

dblp:352/8702 · DBLP profile ↗
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4ranked-venue papers
3as first author
4since 2021 · last 2026
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 4 · 3 first-author · 4 since 2021
YearPublicationVenuePosition
2026 A Multi-rate 2-2 DT-CT MASH DSM Using an Embedded LPF for Easy-Driving
Qingxun Wang, Ziqiang Cai, Yinglong Ding, Liang Qi 0002
ISCAS1
2026 A MASH Two-Phase Incremental ADC with High Tolerance to QN Leakage
Qingxun Wang, Yuhan Pan, Yinglong Ding, Liang Qi 0002
ISCAS1
2023 A Two-step Linear-Exponential Incremental ADC with Slope Extended Counting
abstract
Two-step linear-exponential architectures can be applied to incremental ADCs (IADC) to achieve high resolution. In the first step, the ADC works as a normal first-order IADC while, in the second step, the exponential integrator is used to implement extended counting. There exist two architectures for the implementation of the exponential step, where the only difference depends on whether the input signal is connected or disconnected. By conducting a comparative analysis on such two slightly different linear-exponential architectures, we propose to combine the exponential and slope techniques to further boost the resolution without degrading its original thermal-noise suppression ability and DWA effectiveness. Mathematical analysis and simulation results are presented to confirm the principle of the proposed IADC.
Yuhan Pan, Qingxun Wang, Kaiquan Chen, Jiuchao Qian, Yong Lian 0001, Liang Qi 0002
ISCAS2
2023 A Two-Phase Linear-Exponential Incremental ADC with Second-order Noise Coupling
abstract
This paper presents a two-phase linear-exponential incremental analog-to-digital converter (IADC) with using second-order noise coupling (NC). In the first phase, it works as a first-order IADC. Then the second-order NC path is activated in the second phase to significantly expedite the accumulation speed. Moreover, during the second phase, the integrator is disabled to achieve a large maximum stable amplitude (MSA). Simulations demonstrated that the proposed architecture could achieve a higher signal-to-quantization-noise ratio (SQNR) while avoiding the noise penalty and keeping the high effectiveness of data weighting averaging (DWA) compared with the prior art with using first-order NC. Mathematical analysis and further simulation results are presented to confirm the theory of the proposed structure.
Qingxun Wang, Yuhan Pan, Kaiquan Chen, Liang Qi 0002
ISCAS1