Abstract / truncated to 115 words (read the full abstract)

Due to the extensive growth of big data applications, the widespread use of multisensor technologies, and the need for efficient data representations, multidimensional techniques are a primary tool for many signal processing applications. Multidimensional arrays or tensors allow a natural representation of high-dimensional data. Therefore, they are particularly suited for tasks involving multi-modal data sources such as biomedical sensor readings or multiple-input and multiple-output (MIMO) antenna arrays. While tensor-based techniques were still in their infancy several decades ago, nowadays, they have already proven their effectiveness in various applications. There are many different tensor decompositions in the literature, and each finds use in diverse signal processing fields. In this thesis, we focus on two tensor factorization ... toggle 5 keywords

tensor decomposition MIMO multidimensional signal processing data fusion multilinear algebra

Information

Author
Khamidullina, Liana
Institution
Technische Universit├Ąt Ilmenau
Supervisor
Publication Year
2024
Upload Date
Jan. 26, 2024

First few pages / click to enlarge

The current layout is optimized for mobile phones. Page previews, thumbnails, and full abstracts will remain hidden until the browser window grows in width.

The current layout is optimized for tablet devices. Page previews and some thumbnails will remain hidden until the browser window grows in width.