Low-Rank Decomposition of Multi-Dimensional Arrays

Compared to low-rank matrix decomposition, low-rank decomposition of multi-dimensional arrays has a very attractive feature: it is essentially unique. Discussing theoretical results and intriguing applications, this book introduces readers with a signal processing and communications background to the concepts of low-rank decomposition of multi-dimensional arrays. The author provides historical background and lays the groundwork with coverage of the mathematics and algorithms involved. He then explores the applications in signal processing and communications such as multiple-invariance sensor array processing, blind beamforming, code-blind DS-CDMA, and more.