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20222026
most citedCramer-Rao Lower Bound Optimization for Hidden Moving Target Sensing via Multi-IRS-Aided Radar

29 citations · 86 across the 25 of their papers we have counts for

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Showing 2023 · cs.ITShow all

6 papers · 2 filters

cs.IT2023★ 2 cited

From Quasi-Isometric Embeddings to Finite-Volume Property: A Theoretical Framework for Quantized Matrix Completion

Arian Eamaz, Farhang Yeganegi, Mojtaba Soltanalian

We delve into the impact of memoryless scalar quantization on matrix completion. Our primary motivation for this research is to evaluate the recovery performance of nuclear norm mi…

cs.IT2023

Matrix Completion from One-Bit Dither Samples

Arian Eamaz, Farhang Yeganegi, Mojtaba Soltanalian

We explore the impact of coarse quantization on matrix completion in the extreme scenario of dithered one-bit sensing, where the matrix entries are compared with time-varying thres…

cs.IT2023

Low-rank Matrix Sensing With Dithered One-Bit Quantization

Farhang Yeganegi, Arian Eamaz, Mojtaba Soltanalian

We explore the impact of coarse quantization on low-rank matrix sensing in the extreme scenario of dithered one-bit sampling, where the high-resolution measurements are compared wi…

cs.IT2023

Harnessing the Power of Sample Abundance: Theoretical Guarantees and Algorithms for Accelerated One-Bit Sensing

Arian Eamaz, Farhang Yeganegi, Deanna Needell +1

One-bit quantization with time-varying sampling thresholds (also known as random dithering) has recently found significant utilization potential in statistical signal processing ap…

cs.IT2023

One-Bit Quadratic Compressed Sensing: From Sample Abundance to Linear Feasibility

Arian Eamaz, Farhang Yeganegi, Deanna Needell +1

One-bit quantization with time-varying sampling thresholds has recently found significant utilization potential in statistical signal processing applications due to its relatively…

cs.IT2023★ 13 cited

Quantized Phase-Shift Design of Active IRS for Integrated Sensing and Communications

Zahra Esmaeilbeig, Arian Eamaz, Kumar Vijay Mishra +1

Integrated sensing and communications (ISAC) is a spectrum-sharing paradigm that allows different users to jointly utilize and access the crowded electromagnetic spectrum. In this…