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20132026
most citedDesigning Unimodular Codes via Quadratic Optimization is not Always Hard

225 citations · 888 across the 36 of their papers we have counts for

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Showing 2022Show all

7 papers · 1 filter

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★ 4 cited

Waveform Design for Mutual Interference Mitigation in Automotive Radar

Arindam Bose, Bo Tang, Wenjie Huang +2

The mutual interference between similar radar systems can result in reduced radar sensitivity and increased false alarm rates. To address the synchronous and asynchronous interfere…

quant-ph2022

Quantum Compressive Sensing: Mathematical Machinery, Quantum Algorithms, and Quantum Circuitry

Kyle Sherbert, Naveed Naimipour, Haleh Safavi +2

Compressive sensing is a sensing protocol that facilitates reconstruction of large signals from relatively few measurements by exploiting known structures of signals of interest, t…

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.SP2022★ 9 cited

One-Bit Compressive Sensing: Can We Go Deep and Blind?

Yiming Zeng, Shahin Khobahi, Mojtaba Soltanalian

One-bit compressive sensing is concerned with the accurate recovery of an underlying sparse signal of interest from its one-bit noisy measurements. The conventional signal recovery…