2020 # Rethinking sketching as sampling: A graph signal processing approach

**Abstract:** Sampling of bandlimited graph signals has welldocumented merits for dimensionality reduction, affordable storage, and online processing of streaming network data. Most existing sampling methods are designed to minimize the error incurred when reconstructing the original signal from its samples. Oftentimes these parsimonious signals serve as inputs to computationally-intensive linear operators (e.g., graph filters and transforms). Hence, interest shifts from reconstructing the signal itself towards approximatin…

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“…The GFTx K ofx writes asx K = V H K x. This representation connects the signal bandwidth with the sampling and reconstruction strategies as shown in [12], [14], [15], [29], [30]. We will also exploit bandlimitedness in Section IV to control the network from a few driving nodes.…”

confidence: 99%

“…The GFTx K ofx writes asx K = V H K x. This representation connects the signal bandwidth with the sampling and reconstruction strategies as shown in [12], [14], [15], [29], [30]. We will also exploit bandlimitedness in Section IV to control the network from a few driving nodes.…”

confidence: 99%

“…Lead by the promising results of bandlimited graph signal reconstruction from samples on a few nodes [12], [14], [15], [29], [30], we aim to control x t through a fixed, time-invariant, set of nodes S of cardinality |S| = M ≤ N . Let then B = C T denote a binary matrix that selects these nodes.…”

confidence: 99%