Publications related to Adaptive tracking of linear time-variant systems by extended RLS algorithms

A New Identity for the Least-square Solution of Overdetermined Set of Linear Equations

Afsaneh Asaei, Mohammadjavad Taghizadeh, Saeid Haghighatshoar

In this paper, we prove a new identity for the least-square solution of an over-determined set of linear equation

Ax=b

, where

A

is an

m\times n

full-rank matrix,

b

is a column-vector of dimension

m

, and

m

(the number of equations) is larger tha ...

Idiap2015

Convergence estimates in probability and in expectation for discrete least squares with noisy evaluations at random points

Fabio Nobile, Giovanni Migliorati

We study the accuracy of the discrete least-squares approximation on a finite-dimensional space of a real-valued target function from noisy pointwise evaluations at independent random points distributed according to a given sampling probability measure. Th ...

2015

MATHICSE Technical Report : Convergence estimates in probability and in expectation for discrete least squares with noisy evaluations at random points

Fabio Nobile, Giovanni Migliorati

We study the accuracy of the discrete least-squares approximation on a finite dimensional space of a real-valued target function from noisy pointwise evaluations at independent random points distributed according to a given sampling probability measure. Th ...

MATHICSE2015

Robust distributed detection over adaptive diffusion networks

Ali H. Sayed, Ali Zoubir

Diffusion adaptation techniques based on the least-mean-squares criterion have been proposed for distributed detection of a signal in Gaussian-distributed noise, forgoing the need for a fusion center. However, least-mean-squares solutions are generally non ...

IEEE2014

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

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

Diffusion-based bias-compensated RLS for distributed estimation over adaptive sensor networks

Ali H. Sayed

We present a diffusion-based bias-compensated recursive least squares (RLS) algorithm for distributed estimation in ad-hoc adaptive sensor networks where nodes cooperate to estimate a common deterministic parameter vector. It is assumed that both the regre ...

2011

Distributed Estimation Over an Adaptive Incremental Network Based on the Affine Projection Algorithm

Ali H. Sayed

We study the problem of distributed estimation based on the affine projection algorithm (APA), which is developed from Newton's method for minimizing a cost function. The proposed solution is formulated to ameliorate the limited convergence properties of l ...

IEEE2010

Nonideal sampling and regularized interpolation of noisy data

Sathish Ramani

Conventional sampling (Shannon's sampling formulation and its approximation-theoretic counterparts) and interpolation theories provide effective solutions to the problem of reconstructing a signal from its samples, but they are primarily restricted to the ...

EPFL2009

Phase-step estimation in interferometry via an unscented Kalman filter

Pramod Rastogi, Abhijit Patil

We present an unscented Kalman filter to identify the phase step imparted to a piezoelectric transducer in phase shifting interferometry in the presence of Gaussian noise. The advantage of the proposed algorithm lies in its ability to determine the phase s ...

2009

Adaptive tracking of linear time-variant systems by extended RLS algorithms

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A New Identity for the Least-square Solution of Overdetermined Set of Linear Equations

Convergence estimates in probability and in expectation for discrete least squares with noisy evaluations at random points

MATHICSE Technical Report : Convergence estimates in probability and in expectation for discrete least squares with noisy evaluations at random points

Robust distributed detection over adaptive diffusion networks

Performance Limits for Distributed Estimation Over LMS Adaptive Networks

Diffusion Bias-Compensated RLS Estimation Over Adaptive Networks

Diffusion-based bias-compensated RLS for distributed estimation over adaptive sensor networks

Distributed Estimation Over an Adaptive Incremental Network Based on the Affine Projection Algorithm

Nonideal sampling and regularized interpolation of noisy data

Phase-step estimation in interferometry via an unscented Kalman filter

Diffusion Bias-Compensated RLS Estimation Over Adaptive Networks

Phase-step estimation in interferometry via an unscented Kalman filter

A New Identity for the Least-square Solution of Overdetermined Set of Linear Equations

MATHICSE Technical Report : Convergence estimates in probability and in expectation for discrete least squares with noisy evaluations at random points

Convergence estimates in probability and in expectation for discrete least squares with noisy evaluations at random points

Performance Limits for Distributed Estimation Over LMS Adaptive Networks

Diffusion-based bias-compensated RLS for distributed estimation over adaptive sensor networks

Robust distributed detection over adaptive diffusion networks

Nonideal sampling and regularized interpolation of noisy data

Distributed Estimation Over an Adaptive Incremental Network Based on the Affine Projection Algorithm