Randomized incremental protocols over adaptive networks
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Analytic queueing network models constitute a flexible tool for the study of network flow. These aggregate models are simple to manipulate and their analytic aspect renders them suitable for use within an optimization framework. Analytic queueing network m ...
We consider the problem of distributed Kalman filtering, where a set of nodes are required to collectively estimate the state of a linear dynamic system from their individual measurements. Our focus is on diffusion strategies, where nodes communicate with ...
Analytic queueing network models constitute a flexible tool for the study of network flow. These aggregate models are simple to manipulate and their analytic aspect renders them suitable for use within an optimization framework. Analytic queueing network m ...
We study the mean-square performance of a diffusion least mean-squares protocol proposed in recent work to address the problem of distributed estimation [1, 2]. By relying on energy conservation arguments [8] we derive closed form expressions for the mean- ...
Numerical simulations of the transient operation of an islanded power network subject to load rejections are performed. The islanded power network case study consists of a 1-GW hydroelectric power plant featuring four generating units, a long penstock, and ...
We consider multiple description source coding problem with Gaussian source and mean squared error, for K=3 descriptions. We obtain an outer bound for the rate region of the problem. We also derive an inner bound for the problem based on successively ref ...
In this paper, the steady-state performance of the distributed least mean-squares (dLMS) algorithm within an incremental network is evaluated without the restriction of Gaussian distributed inputs. Computer simulations are presented to verify the derived p ...
Analytic queueing network models often assume infinite capacity for all queues. For real systems this infinite capacity assumption does not hold, but is often maintained due to the difficulty of grasping the between-queue correlation structure present in f ...
This paper uses averaging analysis to study the mean-square performance of adaptive filters, not only in terms of stability conditions but also in terms of expressions for the mean-square error and the mean-square deviation of the filters, as well as in te ...
Affine projection algorithms are useful adaptive filters whose main purpose is to speed the convergence of LMS-type filters. Most analytical results on affine projection algorithms assume special regression models or Gaussian regression data. The available ...
Institute of Electrical and Electronics Engineers2004
