11 papers
On the Sample Complexity of Super-Resolution Radar
Mohammad Mahdi Kamjoo, Saeed Razavi, Sajad Daei
We point out an issue with Lemma 8.6 of [1]. This lemma specifies the required sample complexity for recovering the delay-Doppler pairs in radar systems. In this lemma, it is claim…
Blind Two-Dimensional Super Resolution in Multiple Input Single Output Linear Systems
Shahedeh Sayyari, Sajad Daei, Farzan Haddadi
In this paper, we consider a multiple-input single-output (MISO) linear time-varying system whose output is a superposition of scaled and time-frequency shifted versions of inputs.…
Off-the-grid Recovery of Time and Frequency Shifts with Multiple Measurement Vectors
Maral Safari, Sajad Daei, Farzan Haddadi
We address the problem of estimating time and frequency shifts of a known waveform in the presence of multiple measurement vectors (MMVs). This problem naturally arises in radar im…
Living near the edge: A lower-bound on the phase transition of total variation minimization
Sajad Daei, Farzan Haddadi, Arash Amini
This work is about the total variation (TV) minimization which is used for recovering gradient-sparse signals from compressed measurements. Recent studies indicate that TV minimiza…
A Greedy Algorithm for Matrix Recovery with Subspace Prior Information
Hamideh. S Fazael Ardakani, Sajad Daei, Farzan Haddadi
Matrix recovery is the problem of recovering a low-rank matrix from a few linear measurements. Recently, this problem has gained a lot of attention as it is employed in many applic…
Optimal Weighted Low-rank Matrix Recovery with Subspace Prior Information
Sajad Daei, Arash Amini, Farzan Haddadi
Matrix sensing is the problem of reconstructing a low-rank matrix from a few linear measurements. In many applications such as collaborative filtering, the famous Netflix prize pro…