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Publications associées (83)

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Diffusion Strategies Outperform Consensus Strategies for Distributed Estimation Over Adaptive Networks

Ali H. Sayed

Adaptive networks consist of a collection of nodes with adaptation and learning abilities. The nodes interact with each other on a local level and diffuse information across the network to solve estimation and inference tasks in a distributed manner. In th ...

IEEE2012

Combination weights for diffusion strategies with imperfect information exchange

Ali H. Sayed

Adaptive networks rely on in-network and collaborative processing among distributed agents to deliver enhanced performance in estimation and inference tasks. Information is exchanged among the nodes, usually over noisy links. This paper first investigates ...

IEEE2012

Performance Limits for Distributed Estimation Over LMS Adaptive Networks

Ali H. Sayed

In this work, we analyze the mean-square performance of different strategies for distributed estimation over least-mean-squares (LMS) adaptive networks. The results highlight some useful properties for distributed adaptation in comparison to fusion-based c ...

IEEE2012

Performance limits of LMS-based adaptive networks

Ali H. Sayed

In this work we analyze the mean-square performance of different strategies for adaptation over two-node least-mean-squares (LMS) networks. The results highlight some interesting properties for adaptive networks in comparison to centralized solutions. The ...

IEEE2011

Diffusion Bias-Compensated RLS Estimation Over Adaptive Networks

Ali H. Sayed

We study the problem of distributed least-squares estimation over ad hoc adaptive networks, where the nodes have a common objective to estimate and track a parameter vector. We consider the case where there is stationary additive colored noise on both the ...

IEEE2011

Optimal combination rules for adaptation and learning over networks

Ali H. Sayed

Adaptive networks, consisting of a collection of nodes with learning abilities, are well-suited to solve distributed inference problems and to model various types of self-organized behavior observed in nature. One important issue in designing adaptive netw ...

IEEE2011

Randomized incremental protocols over adaptive networks

Ali H. Sayed

We introduce an incremental cooperation mode into the framework of adaptive networks (AN). The method applies to generic topologies and avoids the need to establish a Hamiltonian cycle over the network, generalizing the original incremental mode, while kee ...

IEEE2010

Diffusion Strategies for Distributed Kalman Filtering and Smoothing

Ali H. Sayed

We study the problem of distributed Kalman filtering and smoothing, where a set of nodes is required to estimate the state of a linear dynamic system from in a collaborative manner. Our focus is on diffusion strategies, where nodes communicate with their d ...

IEEE2010

Persistence length and scaling properties of single-stranded DNA adsorbed on modiﬁed graphite

Giovanni Dietler, Guillaume Witz, Kristian Rechendorff

We have characterized the polymer physics of single-stranded DNA (ssDNA) using atomic force microscopy. The persistence length l(p) of circular ssDNA adsorbed on a modified graphite surface was determined independently of secondary structure. At a very low ...

2009

Isometry groups of non-positively curved spaces: Discrete subgroups

Nicolas Monod

We study lattices in non-positively curved metric spaces. Borel density is established in that setting as well as a form of Mostow rigidity. A converse to the flat torus theorem is provided. Geometric arithmeticity results are obtained after a detour throu ...

2009