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20192023
most citedOne-Bit Phase Retrieval: More Samples Means Less Complexity?

27 citations · 49 across the 8 of their papers we have counts for

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7 papers · 1 filter

eess.SP2023

Near-Field Low-WISL Unimodular Waveform Design for Terahertz Automotive Radar

Arian Eamaz, Farhang Yeganegi, Kumar Vijay Mishra +1

Conventional sensing applications rely on electromagnetic far-field channel models with plane wave propagation. However, recent ultra-short-range automotive radar applications at u…

eess.SP2022★ 5 cited

UNO: Unlimited Sampling Meets One-Bit Quantization

Arian Eamaz, Kumar Vijay Mishra, Farhang Yeganegi +1

Recent results in one-bit sampling provide a framework for a relatively low-cost, low-power sampling, at a high rate by employing time-varying sampling threshold sequences. Another…

eess.SP2022★ 7 cited

ORKA: Accelerated Kaczmarz Algorithms for Signal Recovery from One-Bit Samples

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…

eess.SP2022

Covariance Recovery for One-Bit Sampled Data With Time-Varying Sampling Thresholds-Part II: Non-Stationary Signals

Arian Eamaz, Farhang Yeganegi, Mojtaba Soltanalian

The recovery of the input signal covariance values from its one-bit sampled counterpart has been deemed a challenging task in the literature. To deal with its difficulties, some as…

eess.SP2022

Covariance Recovery for One-Bit Sampled Data With Time-Varying Sampling Thresholds-Part I: Stationary Signals

Arian Eamaz, Farhang Yeganegi, Mojtaba Soltanalian

One-bit quantization, which relies on comparing the signals of interest with given threshold levels, has attracted considerable attention in signal processing for communications an…

eess.SP2022★ 27 cited

One-Bit Phase Retrieval: More Samples Means Less Complexity?

Arian Eamaz, Farhang Yeganegi, Mojtaba Soltanalian

The classical problem of phase retrieval has found a wide array of applications in optics, imaging and signal processing. In this paper, we consider the phase retrieval problem in…

eess.SP2019★ 10 cited

Detection and Statistical Modeling of Birth-Death Anomaly

Salman Mohamadi, Farhang Yeganegi, Nasser M Nasrabadi

Generally, anomaly detection has a great importance particularly in applied statistical signal processing. Here we provide a general framework in order to detect anomaly through th…