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Diffusion Strategies for Distributed Kalman Filtering and Smoothing

Publications associées (32)

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General direction-of-arrival tracking with acoustic nodes

Volkan Cevher

In this paper, we propose a particle filter acoustic direction-of-arrival (DOA) tracker to track multiple maneuvering targets using a state space approach. The particle filter determines its state vector using a batch of DOA estimates. The filter likelihoo ...

Institute of Electrical and Electronics Engineers2005

New algorithmic methods for real-time transportation problems

Frank Crittin

Two of the most basic problems encountered in numerical optimization are least-squares problems and systems of nonlinear equations. The use of more and more complex simulation tools on high performance computers requires solving problems involving an incre ...

EPFL2004

General state-space models

Thomas Gsponer

In time series analysis state-space models provide a wide and flexible class. The basic idea is to describe an unobservable phenomenon of interest on the basis of noisy data. The first constituent of such a model is the so-called state equation, which char ...

EPFL2004

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

Ability of adaptive filters to track carrier offsets and channel nonstationarities

Ali H. Sayed

This paper studies the tracking performance of adaptive filters operating in the presence of two sources of nonstationarities: carrier frequency offsets and random channel variations. Both impairments are common in digital communications due to mismatches ...

IEEE2002

A framework for state-space estimation with uncertain models

Ali H. Sayed

Develops a framework for state-space estimation when the parameters of the underlying linear model are subject to uncertainties. Compared with existing robust filters, the proposed filters perform regularization rather than deregularization. It is shown th ...

Institute of Electrical and Electronics Engineers2001

Robust FxLMS algorithms with improved convergence performance

Ali H. Sayed

This paper proposes two modifications of the filtered-x least mean squares (FxLMS) algorithm with improved convergence behavior albeit at the same computational cost of 2M operations per time step as the original FxLMS update. The paper further introduces ...

IEEE1998

An l2-stable feedback structure for nonlinear adaptive filtering and identification

Ali H. Sayed

This paper proposes a feedback structure for the design of l2-stable algorithms for nonlinear adaptive filtering and identification, and establishes explicit connections between classical schemes in IIR modeling and more recent results in H∞ theory. In par ...

Elsevier1997

Robustness of Gauss—Newton recursive methods: A deterministic feedback analysis

Ali H. Sayed

This paper provides a time-domain feedback analysis of the robustness performance of Gauss-Newton recursive methods that are often used in identification and control. These are recursive estimators that also involve updates of sample covariance matrices. S ...

Elsevier1996