With the development of modern advanced radar, there are high demands to perform
inverse synthetic aperture radar (ISAR) imaging from sparse frequency band (SFB) and …

There has been an increasing interest in addressing the issue of high-resolution inverse
synthetic aperture radar (ISAR) imaging from sparse sampling data. Traditional compressed …

The paper proposes a new approach for the recovery of missing data from phasor
measurement units (PMUs). The approach is based on the application of tensor …

We give a new framework for solving the fundamental problem of low-rank matrix
completion, ie, approximating a rank-r matrix M∈R^m*n (where m≧n) from random …

Time series prediction has been a long-standing research topic and an essential application
in many domains. Modern time series collected from sensor networks (eg, energy …

Robust low-rank matrix completion (RMC), or robust principal component analysis with
partially observed data, has been studied extensively for computer vision, signal processing …

Modern Smart Grids incorporate physical power grids and cyber systems, creating a cyber-
physical system. phasor measurement units (PMUs) transmit time synchronized …

We study the robust matrix completion problem for the low-rank Hankel matrix, which detects
the sparse corruptions caused by extreme outliers while we try to recover the original Hankel …

Automotive radar plays an important role in the field of advanced driver assistant systems
(ADASs), in the detection of unmanned aerial vehicles (UAV), and so on. Most automotive …

With the rapid development of vibration and noise reduction technologies, underwater target
detection is facing great challenges. Particularly, the task of high-resolution direction of …