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Distributed pareto-optimal solutions via diffusion adaptation

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Beam coordination via diffusion adaptation over array networks

Ali H. Sayed

In this work, we consider a distributed beam coordination problem, where a collection of arrays are interconnected by a certain topology. The beamformers employ an adaptive diffusion strategy to compute the beamforming weight vectors by relying solely on c ...

IEEE2012

On the effects of topology and node distribution on learning over complex 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 through their collaborations, as dictated by the network topology and ...

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

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

Recursive Implementation of the Distributed Karhunen-Loeve Transform

Michael Christoph Gastpar

In the distributed linear source coding problem, a set of distributed sensors observe subsets of a data vector with noise, and provide the fusion center linearly encoded data. The goal is to determine the encoding matrix of each sensor such that the fusion ...

2010

Monte-Carlo SURE: A Black-Box Optimization of Regularization Parameters for General Denoising Algorithms

Michaël Unser, Thierry Blu, Sathish Ramani

We consider the problem of optimizing the parameters of a given denoising algorithm for restoration of a signal corrupted by white Gaussian noise. To achieve this, we propose to minimize Stein's unbiased risk estimate (SURE) which provides a means of asses ...

IEEE2008

Steady-State Performance of Adaptive Diffusion Least-Mean Squares

Ali H. Sayed

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- ...

IEEE2007

Mean-Square Performance of a Family of Affine Projection Algorithms

Ali H. Sayed

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

Mean-square performance of adaptive filters using averaging theory

Ali H. Sayed

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 ...

IEEE2004

Transient analysis of data-normalized adaptive filters

Ali H. Sayed

Abstract: This paper develops an approach to the transient analysis of adaptive filters with data normalization. Among other results, the derivation characterizes the transient behavior of such filters in terms of a linear time-invariant state-space model ...

IEEE2003