Distributed Compressive Sensing: Performance Analysis With Diverse Signal Ensembles
梁惟㨗教授東海大學應用數學系 15:30 – 17:00 鴻經館 M107Abstract：
Distributed compressive sensing (DCS) is a framework that considers joint sparsity within signal ensembles along with multiple measurement vectors (MMVs). However, current theoretical bounds of the probability of perfect recovery for MMVs are derived to be essentially identical to that of a single MV (SMV). In this talk, I will introduce two key ingredients, called “Euclidean distances between signals” and “decay rate of signal ensemble,” to conduct a performance analysis of a deterministic signal model under the MMVs framework.