The aim of this thesis is to introduce a variety of signal processing methodologies specifically designed to model, interpret, and learn from data structured within topological spaces. These spaces are loosely characterized as a collection of points together with a neighborhood notion among points. The methodologies and tools discussed herein hold particular relevance and utility…
Everyday sounds in real-world environments are a powerful source of information by which humans can interact with their environments. Humans can infer what is happening around them by listening to everyday sounds. At the same time, it is a challenging task for a computer algorithm in a smart device to automatically recognise, understand, and interpret…
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…
