no code implementations • 13 Mar 2024 • Arian Eamaz, Farhang Yeganegi, Yunqiao Hu, Mojtaba Soltanalian, Shunqiao Sun
This paper investigates the effects of coarse quantization with mixed precision on measurements obtained from sparse linear arrays, synthesized by a collaborative automotive radar sensing strategy.
no code implementations • 9 Dec 2023 • Arian Eamaz, Farhang Yeganegi, Yunqiao Hu, Shunqiao Sun, Mojtaba Soltanalian
The design of sparse linear arrays has proven instrumental in the implementation of cost-effective and efficient automotive radar systems for high-resolution imaging.
no code implementations • 7 Sep 2023 • Arian Eamaz, Farhang Yeganegi, Mojtaba Soltanalian
Additionally, we introduce a sufficient condition specifically designed for UNO sampling to perfectly recover non-bandlimited signals within spline spaces.
no code implementations • 8 Mar 2023 • Arian Eamaz, Farhang Yeganegi, Kumar Vijay Mishra, Mojtaba Soltanalian
Conventional sensing applications rely on electromagnetic far-field channel models with plane wave propagation.
no code implementations • 16 Mar 2022 • 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.
no code implementations • 16 Mar 2022 • Arian Eamaz, Farhang Yeganegi, Mojtaba Soltanalian
Similar to the case of the arcsine law, the Bussgang law only considers a zero sampling threshold.
no code implementations • 9 Aug 2019 • Salman Mohamadi, Farhang Yeganegi, Hamidreza Amindavar
This paper provides a framework in order to statistically model sequences from human genome, which is allowing a formulation to synthesize gene sequences.