Discrete signal processing on graph: multiresolution analysis

Spring 2014

Student
Niv Zehngut
Advisor
Jelena Kovačević
Project description

The theory of discrete signal processing on graphs offers a new paradigm for the analysis of high-dimensional numerical data with complex, irregular structure. The framework extends fundamental signal processing concepts from signals residing on regular lattices, which are studied by the classical signal processing theory, to data residing on general graphs. This theory offers a new methodology for formulating and solving data analysis problems, such as data compression, denoising, reconstruction, classification, anomaly detection, and others, as standard signal processing tasks. The task for this project is to review the literature on the multiresolution analysis and propose a preliminary methodology of doing multiresolution analysis on graphs.

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