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A common problem in network analysis is detecting small subgraphs of interest within a large background graph. This includes multi-source fusion scenarios where data from several modalities must be integrated to form the network. This paper presents an application of novel techniques leveraging the signal processing for graphs algorithmic framework, to well-studied collaboration networks in the field...
The National Aeronautics and Space Administration (NASA) Cyclone Global Navigation Satellite System (CYGNSS) mission aims to understand the coupling between ocean surface properties, moist atmospheric thermodynamics, radiation, and convective dynamics in the inner core of tropical cyclones (TCs). The mission is comprised of eight microsatellites (μSats) in low-earth orbit (LEO) at an inclination of...
This paper outlines techniques for optimization of filter coefficients in a spectral framework for anomalous subgraph detection. Restricting the scope to the detection of a known signal in i.i.d. noise, the optimal coefficients for maximizing the signal's power are shown to be found via a rank-1 tensor approximation of the subgraph's dynamic topology. While this technique optimizes our power metric,...
The problem of detecting a small, anomalous subgraph within a large background network is important and applicable to many fields. The non-Euclidean nature of graph data, however, complicates the application of classical detection theory in this context. A recent statistical framework for anomalous subgraph detection uses spectral properties of a graph's modularity matrix to determine the presence...
The T2K Fine Grained Detector is an active neutrino target that uses segmented scintillator bars to observe short-range particle tracks. 8448 multi-pixel photon counters coupled to wavelength shifting fibres detect scintillator light. An application specific integrated circuit shapes the MPPC waveform and uses a switched capacitor array to store up to 511 analog samples over 10.24μs. High and low...
Graphs are canonical examples of high-dimensional non-Euclidean data sets, and are emerging as a common data structure in many fields. While there are many algorithms to analyze such data, a signal processing theory for evaluating these techniques akin to detection and estimation in the classical Euclidean setting remains to be developed. In this paper we show the conceptual advantages gained by formulating...
The modeling of noise in the frequency domain gives the mean square noise current of a transistor as a function of frequency. RTS in nanoscale devices is easiest modeled as an instantaneous fluctuation in threshold voltage due to the capture and emission of traps. The capture and emission of a single electron at an interface or oxide trap in a nanoscale NMOS transistor is equivalent to a discrete...
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