Browsing by Author "Charalambous, Themistoklis"
Now showing items 1-10 of 10
-
Conference Object
Asymptotic Reverse-Waterfilling Characterization of Nonanticipative Rate Distortion Function of Vector-Valued Gauss-Markov Processes with MSE Distortion
Stavrou, Photios A.; Charalambous, Themistoklis; Charalambous, Charalambos D.; Loyka, Sergey; Skoglund, Mikael (IEEE, 2018)In this paper, we revisit the asymptotic reverse-waterfilling characterization of the nonanticipative rate distortion function (NRDF) derived for a time-invariant multidimensional Gauss-Markov processes with mean-squared ...
-
Article
Delay- and Diversity-Aware Buffer-Aided Relay Selection Policies in Cooperative Networks
Nomikos, Nikolaos; Poulimeneas, Dimitrios; Charalambous, Themistoklis; Krikidis, Ioannis; Vouyioukas, Demosthenes; Johansson, Mikael (2018)Buffer-Aided (BA) relaying has shown tremendous performance improvements in terms of throughput and outage probability, although it has been criticized of suffering from long delays that are restrictive for applications, ...
-
Article
Distributed Averaging and Balancing in Network Systems: with Applications to Coordination and Control
Hadjicostis, Christoforos N.; Domínguez-García, Alejandro D.; Charalambous, Themistoklis (2018)Distributed Averaging and Balancing in Network Systems: with Applications to Coordination and Control
-
Article
Finite-Time Nonanticipative Rate Distortion Function for Time-Varying Scalar-Valued Gauss-Markov Sources
Stavrou, Photios A.; Charalambous, Themistoklis; Charalambous, Charalambos D. (2018)We derive the finite-time horizon nonanticipative rate distortion function (NRDF) of timevarying scalar Gauss-Markov sources under an average mean squared-error (MSE) distortion fidelity. Further, we show that a conditionally ...
-
Conference Object
A General Coding Scheme for Signaling Gaussian Processes Over Gaussian Decision Models
Charalambous, Charalambos D.; Kourtellaris, Christos K.; Charalambous, Themistoklis (IEEE, 2018)In this paper, we transform the n-finite transmission feedback information (FTFI) capacity of unstable Gaussian decision models with memory on past outputs, subject to an average cost constraint of quadratic form derived ...
-
Article
Infinite Horizon Average Cost Dynamic Programming Subject to Total Variation Distance Ambiguity
Tzortzis, Ioannis; Charalambous, Charalambos D.; Charalambous, Themistoklis (2019)We analyze the per unit-time infinite horizon average cost Markov control model, subject to a total variation distance ambiguity on the controlled process conditional distribution. This stochastic optimal control problem ...
-
Conference Object
Laplacian-based matrix design for finite-time average consensus in digraphs
Charalambous, Themistoklis; Hadjicostis, Christoforos N. (2018)In this paper, we consider the problem of assigning time-varying weights on the links of a time-invariant digraph, such that average consensus is reached in a finite number of steps. More specifically, we derive a finite ...
-
Article
Optimal Estimation via Nonanticipative Rate Distortion Function and Applications to Time-Varying Gauss--Markov Processes
Stavrou, Photios A.; Charalambous, Themistoklis; Charalambous, Charalambos D.; Loyka, Sergey (2018)In this paper, we develop finite-time horizon causal filters for general processes taking values in Polish spaces using the nonanticipative rate distortion function ($NRDF$). Subsequently, we apply the $NRDF$ to design ...
-
Conference Object
Privacy-Preserving Average Consensus over Digraphs in the Presence of Time Delays
Charalambous, Themistoklis; Manitara, Nikolas E.; Hadjicostis, Christoforos N. (2019)In this paper, we propose a privacy-preserving discrete-time asymptotic average consensus mechanism that allows components of a multi-component system to calculate the exact average of their initial values without revealing ...
-
Conference Object
When to stop iterating in digraphs of unknown size? An application to finite-time average consensus
Charalambous, Themistoklis; Hadjicostis, Christoforos N. (2018)In multi-agent systems, existing distributed algorithms for finite-time average consensus allow the agents to calculate the exact average in finite time, but typically require the agents to continue the iterative process ...