Publications related to Are ensemble-average learning curves reliable in evaluating the performance of adaptive filters?

Reconstruction of 3D scattered data via radial basis functions by efficient and robust techniques

We propose new algorithms to overcome two of the most constraining limitations of surface reconstruction methods in use. In particular, we focus on the large amount of data characterizing standard acquisitions by scanner and the noise intrinsically introdu ...

Elsevier Science Bv2017

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 ...

2015

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

Discrete least squares polynomial approximation with random evaluations − application to parametric and stochastic elliptic PDEs

Fabio Nobile, Giovanni Migliorati

Motivated by the numerical treatment of parametric and stochastic PDEs, we analyze the least-squares method for polynomial approximation of multivariate functions based on random sampling according to a given probability measure. Recent work has shown that ...

2015

From averaging to acceleration, there is only a step-size

Nicolas Henri Bernard Flammarion

We consider the optimization of a quadratic objective function whose gradients are only accessible through a stochastic oracle that returns the gradient at any given point plus a zero-mean finite variance random error. We present the first algorithm that a ...

2015

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

MATHICSE Technical Report : Discrete least squares polynomial approximation with random evaluations – application to parametric and stochastic elliptic PDES

Fabio Nobile, Giovanni Migliorati

Motivated by the numerical treatment of parametric and stochastic PDEs, we analyze the least-squares method for polynomial approximation of multivariate func- tions based on random sampling according to a given probability measure. Recent work has shown th ...

MATHICSE2014

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

Adaptive processing over distributed networks

Ali H. Sayed

The article describes recent adaptive estimation algorithms over distributed networks. The algorithms rely on local collaborations and exploit the space-time structure of the data. Each node is allowed to communicate with its neighbors in order to exploit ...

The Institute of Electronics, Information and Communication Engineers2007

Are ensemble-average learning curves reliable in evaluating the performance of adaptive filters?

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Reconstruction of 3D scattered data via radial basis functions by efficient and robust techniques

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

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

Discrete least squares polynomial approximation with random evaluations − application to parametric and stochastic elliptic PDEs

From averaging to acceleration, there is only a step-size

Robust distributed detection over adaptive diffusion networks

MATHICSE Technical Report : Discrete least squares polynomial approximation with random evaluations – application to parametric and stochastic elliptic PDES

Performance Limits for Distributed Estimation Over LMS Adaptive Networks

Diffusion Bias-Compensated RLS Estimation Over Adaptive Networks

Adaptive processing over distributed networks

Discrete least squares polynomial approximation with random evaluations − application to parametric and stochastic elliptic PDEs

Reconstruction of 3D scattered data via radial basis functions by efficient and robust techniques

From averaging to acceleration, there is only a step-size

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

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

Robust distributed detection over adaptive diffusion networks

Performance Limits for Distributed Estimation Over LMS Adaptive Networks

MATHICSE Technical Report : Discrete least squares polynomial approximation with random evaluations – application to parametric and stochastic elliptic PDES

Diffusion Bias-Compensated RLS Estimation Over Adaptive Networks

Adaptive processing over distributed networks