no code implementations • 18 Dec 2023 • Satish Mulleti, Timur Zirtiloglu, Arman Tan, Rabia Tugce Yazicigil, Yonina C. Eldar
Analog-to-digital converters (ADCs) facilitate the conversion of analog signals into a digital format.
no code implementations • 22 Nov 2023 • Satish Mulleti, Resham Yashwanth Kumar, Laxmeesha Somappa
An alternative method using phase modulation (PM) achieves HDR-ADC functionality by modulating the phase of a carrier signal with the analog input.
no code implementations • 4 Sep 2023 • Garweet Sresth, Ajit Rajwade, Satish Mulleti
We present an estimator to solve for the unknown vector.
no code implementations • 3 Jul 2023 • Kaushani Majumder, SibiRaj B. Pillai, Satish Mulleti
A greedy selection (GS) algorithm is widely used to select sensors in homogeneous sensor networks.
1 code implementation • National Conference on Communications (NCC) 2023 • Archishman Biswas, A P Goutham, Saket Pateriya, Divyang Sureshbhai Jadav, Satish Mulleti, Vikram M. Gadre
The reported performance metrics show the improvement achieved by using our proposed embedding network and fusing both sides of occluded ear images.
no code implementations • 23 Jan 2023 • Satish Mulleti, Eliya Reznitskiy, Shlomi Savariego, Moshe Namer, Nimrod Glazer, Yonina C. Eldar
The dynamic range of an ADC also plays an important role, and ideally, it should be greater than the signal's; otherwise, the signal will be clipped.
no code implementations • 28 Sep 2022 • Bahareh Tolooshams, Satish Mulleti, Demba Ba, Yonina C. Eldar
To reduce its computational and implementation cost, we propose a compression method that enables blind recovery from much fewer measurements with respect to the full received signal in time.
no code implementations • 18 Jul 2022 • Satish Mulleti, Yonina C. Eldar
In the context of modulo folding for FRI sampling, existing works operate at a very high sampling rate compared to the rate of innovation (RoI) and require a large number of samples compared to the degrees of freedom (DoF) of the FRI signal.
no code implementations • 29 Jun 2022 • Eyar Azar, Satish Mulleti, Yonina C. Eldar
We show that our algorithm has the lowest mean-squared error while recovering the signal for a given sampling rate, noise level, and dynamic range of the compared to existing algorithms.
no code implementations • 7 Oct 2021 • Eyar Azar, Satish Mulleti, Yonina C. Eldar
Existing recovery algorithms to recover the signal from its modulo samples operate at a high sampling rate and are not robust in the presence of noise.
no code implementations • 28 Jun 2021 • Satish Mulleti, Haiyang Zhang, Yonina C. Eldar
Typically, Fourier samples of the FRI signals are used for reconstruction.
no code implementations • 22 Oct 2020 • Bahareh Tolooshams, Satish Mulleti, Demba Ba, Yonina C. Eldar
We propose a learned-structured unfolding neural network for the problem of compressive sparse multichannel blind-deconvolution.