In recent years, compressive sensing attracts intensive attentions in the field of statistics, automatic control, data mining and machine learning. It assumes the sparsity of the ...
We study the distributed sampling and centralized reconstruction of two correlated signals, modeled as the input and output of an unknown sparse filtering operation. This is akin ...
Ali Hormati, Olivier Roy, Yue M. Lu, Martin Vetter...
This paper addresses the problem of Through-the-Wall Radar Imaging (TWRI) using the Multiple-Measurement Vector (MMV) compressive sensing model. TWR image formation is reformulate...
Jie Yang, Abdesselam Bouzerdoum, Fok Hing Chi Tivi...
Abstract. We relate two well-studied methodologies in deductive verification of operationally modeled sequential programs, namely the use of inductive invariants and clock functio...
This paper describes a low-complexity approach for reconstructing average packet arrival rates and instantaneous packet counts at a router in a communication network, where the arr...
Maxim Raginsky, Sina Jafarpour, Rebecca Willett, A...