Publications related to Adaptive estimation algorithms over distributed networks

The effect of overall stimulus configuration on crowding

Michael Herzog, Maya Roinishvili, Mattew Pachai

The standard framework to study vision is typically hierarchical and feedforward, which facilitates deconstructing complex mechanisms into smaller, more tractable problems. However, this framework can fail when elements are presented in context, as they ar ...

2017

A Functional Framework for Enhanced Ultrasound Imaging

Ultrasound systems are cheap, portable, and fast, which have become impressively popular over the last decades. State-of art imaging is however known to be sub-optimal. Most attempts to improve it formulate the problem on a discrete spatial grid and suffer ...

2017

Aesthetics – as a dimension of society and a component of spatial theory

Mirza Tursic

The title of this paper suggests three things. First, that society’s issues are multidimensional i.e. society being a multidimensional system in a way that each dimension undergo the totality of society’s. These dimensions hold together social systems of v ...

2016

Locating Faults on Untransposed, Meshed Transmission Networks Using a Limited Number of Synchrophasor Measurements

Mario Paolone, Sadegh Azizi

The method of symmetrical components is not effective for fault location in the case of untransposed lines, due to potential couplings between the sequence circuits. This paper proposes a non-iterative algorithm in the phase-coordinates for wide-area fault ...

Institute of Electrical and Electronics Engineers2016

The recursive Hessian sketch for adaptive filtering

Martin Vetterli, Robin Scheibler

We introduce in this paper the recursive Hessian sketch, a new adaptive filtering algorithm based on sketching the same exponentially weighted least squares problem solved by the recursive least squares algorithm. The algorithm maintains a number of sketch ...

Ieee2016

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

Adaptive estimation algorithms over distributed networks

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The effect of overall stimulus configuration on crowding

A Functional Framework for Enhanced Ultrasound Imaging

Aesthetics – as a dimension of society and a component of spatial theory

Locating Faults on Untransposed, Meshed Transmission Networks Using a Limited Number of Synchrophasor Measurements

The recursive Hessian sketch for adaptive filtering

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

Aesthetics – as a dimension of society and a component of spatial theory

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

Robust distributed detection over adaptive diffusion networks

A Functional Framework for Enhanced Ultrasound Imaging

The recursive Hessian sketch for adaptive filtering

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

Locating Faults on Untransposed, Meshed Transmission Networks Using a Limited Number of Synchrophasor Measurements

The effect of overall stimulus configuration on crowding