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A Class of Prediction-Correction Methods for Time-Varying Convex Optimization
Andrea Simonetto, Aryan Mokhtari, Alec Koppel +2
This paper considers unconstrained convex optimization problems with time-varying objective functions. We propose algorithms with a discrete time-sampling scheme to find and track…
Distributed Autoregressive Moving Average Graph Filters
Andreas Loukas, Andrea Simonetto, Geert Leus
We introduce the concept of autoregressive moving average (ARMA) filters on a graph and show how they can be implemented in a distributed fashion. Our graph filter design philosoph…
Sensor Selection for Estimation with Correlated Measurement Noise
Sijia Liu, Sundeep Prabhakar Chepuri, Makan Fardad +3
In this paper, we consider the problem of sensor selection for parameter estimation with correlated measurement noise. We seek optimal sensor activations by formulating an optimiza…
Reconstruction of Graph Signals through Percolation from Seeding Nodes
Santiago Segarra, Antonio G. Marques, Geert Leus +1
New schemes to recover signals defined in the nodes of a graph are proposed. Our focus is on reconstructing bandlimited graph signals, which are signals that admit a sparse represe…
Achievable Rates of Multi-User Millimeter Wave Systems with Hybrid Precoding
Ahmed Alkhateeb, Robert W. Heath, Geert Leus
Millimeter wave (mmWave) systems will likely employ large antenna arrays at both the transmitters and receivers. A natural application of antenna arrays is simultaneous transmissio…
Sampling of graph signals with successive local aggregations
Antonio G. Marques, Santiago Segarra, Geert Leus +1
A new scheme to sample signals defined in the nodes of a graph is proposed. The underlying assumption is that such signals admit a sparse representation in a frequency domain relat…