Weekly Seminar – 3/24/2017 – Low Rank and Sparse Signal Processing #2

The weekly seminar series resumes after the spring break with a talk on Graph Signal Processing by Rahul Singh from Dr. Dogandzic’s research group. The details are as follows:
Date: March 24th, Friday
Time: 3:00 – 4:00 pm
Venue: 2222 Coover hall
Rahul’s abstract:  Graph Signal Processing (GSP) is concerned with modeling, representation, and processing of signals defined on irregular structures, known as graphs. In this setting, we deal with graph signals which are collection of data values lying on the vertices of arbitrary graphs. Graph signals can be defined as temperatures within a geographical area, traffic capacities at hubs in a transportation network, or human behaviors in a social network. In the talk, we will discuss the existing graph signal processing tools and concepts such as graph Fourier transform, spectral graph wavelets. Following references are good starting point for graph signal processing.

1. David I Shuman et al. “The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains”. In: Signal Processing Magazine, IEEE 30.3 (2013), pp. 83–98.

2. A. Sandryhaila and J.M.F. Moura. “Discrete Signal Processing on Graphs: Frequency Analysis”. In: Signal Processing, IEEE Transactions on 62.12 (2014), pp. 3042–3054.

3. David I Shuman, Benjamin Ricaud, and Pierre Vandergheynst. “Vertex-frequency analysis on graphs”. In: Applied and Computational Harmonic Analysis 40.2 (2016), pp. 260–291.

Slides: GSP

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