Publication

Diffusion Strategies for Distributed Kalman Filtering and Smoothing

Publications associées (32)

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Connectez-vous pour utiliser Chat avec Graph Search

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 distributed Kalman filtering with adaptive weights

Ali H. Sayed

We study 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 measurements. In diffusion Kalman filtering strategies, neighboring state estimates are linearl ...

IEEE2009

A Simple Alternative Derivation of the Expectation Correction Algorithm

Bertrand Mesot

The switching linear dynamical system (SLDS) is a popular model in time-series analysis. However, the complexity of inferring the state of the latent variables scales exponentially with the length of the time-series, resulting in many approximation strateg ...

2009

Diffusion strategies for distributed Kalman filtering: formulation and performance analysis

Ali H. Sayed

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 ...

2008

Mixed-mode implementation of particle filters

Volkan Cevher

In this paper, we develop new mixed-mode implementations for particle filters and compare them to a digital implementation. The motivation for the mixed-mode implementation is to achieve low-power implementation of particle filters. The specific applicatio ...

2007

Acoustic multi target tracking using direction-of-arrival batches

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 Engineers2007

Target tracking using a joint acoustic video system

Volkan Cevher

In this paper, we present a particle filter that exploits multi modal information for robust target tracking. We demonstrate a Bayesian framework for combining acoustic and video information using a state space approach. A proposal strategy for joint acous ...

2007

Mean-square performance of a convex combination of two adaptive filters

Ali H. Sayed

Combination approaches provide an interesting way to improve adaptive filter performance. In this paper, we study the mean-square performance of a convex combination of two transversal filters. The individual filters are independently adapted using their o ...

Institute of Electrical and Electronics Engineers2006

Multi target direction-of-arrival tracking using road priors

Volkan Cevher

In this paper, we present a multi target particle filter DOA tracker that can incorporate road prior information at a single array node. The filter uses a batch of DON's to determine the state vector, based on an image template matching idea. The filter li ...

2006

An acoustic multiple target tracker

Volkan Cevher

We propose a particle filter acoustic tracker to track multiple maneuvering targets using a state space formulation with a locally linear motion model. The observations are a batch of direction-of-arrival (DOA) estimates at various frequencies. The data li ...

2005