SIGNAL PROCESSING OVER DYNAMIC GRAPHS (2025)
Abstract / truncated to 115 words
Extending the concepts of classical signal processing to graphs, a wide array of methods have come to the fore, including filtering, reconstruction, classification, and sampling. Existing approaches in graph signal processing consider a known and static topology, i.e., fixed number of nodes and a fixed edge support. Two types of tasks stand out, namely, topology inference, where the edge support along with their weights are estimated from signals; and data processing, where existing data and the known topology are used to perform different tasks. However, such tasks become quite challenging when the network size and support changes over time. Particularly, these challenges involve adapting to the changing topology, data distributions and dealing with unknown topological ...
graph signal processing – dynamic graphs – expanding graphs – unknown edge support – stochastic attachment – graph filter design – topology decomposition – latent graphs
Information
- Author
- Das, Bishwadeep
- Institution
- TU Delft
- Supervisors
- Publication Year
- 2025
- Upload Date
- March 12, 2025
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