Publication

Transient analysis of data-normalized adaptive filters

Related publications (47)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Intricacies of Describing Weak Interactions involving Halogen Atoms within Density Functional Theory

Ursula Röthlisberger, Ivano Tavernelli

In this work we assess the performance of different dispersion-corrected DFT approaches (M06, M06-2X, DFT-D3 and DCACP) in reproducing high-level wave function based benchmark calculations on the weakly bound halogen dimers (X2)2 and X2-Ar (for X=F,Cl,Br,I ...

Amer Chemical Soc2013

Mean-square analysis of continuous-time distributed estimation strategies

Ali H. Sayed

In this work, we study the mean-square-error performance of a diffusion strategy for continuous-time estimation over networks. We derive differential equations that describe the evolution of the mean and correlation of the weight-error vector, and provide ...

IEEE2012

Diffusion LMS for source and process estimation in sensor networks

Ali H. Sayed

We develop a least mean-squares (LMS) diffusion strategy for sensor network applications where it is desired to estimate parameters of physical phenomena that vary over space. In particular, we consider a regression model with space-varying parameters that ...

IEEE2012

Distributed pareto-optimal solutions via diffusion adaptation

Ali H. Sayed

We consider solving multi-objective optimization problems in a distributed manner over a network of nodes. The problem is equivalent to optimizing a global cost that is the sum of individual components. Diffusion adaptation enables the nodes to cooperate l ...

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

Effects of service loading on the behaviour of a suspension bridge

Ian Smith, Ngoc Thanh Trinh, Irwanda Laory

In order to achieve reliable information about deterioration, it is important to differentiate between changes in structural behaviour due to service loading (temperature, wind and traffic) and changes resulting from damage when interpreting measurement da ...

2011

Robust binary regression

Stephan Morgenthaler, Sahar Hosseinian Ehrensberger

Robust procedures increase the reliability of the results of a data analysis. We studied such a robust procedure for binary regression models based on the criterion of least absolute deviation. The resulting estimating equation consists in a simple modific ...

Elsevier2011

On multivariate calibration with unlabeled data

Dominique Bonvin, Michael Amrhein, Pamandeep Singh Gujral

In principal component regression (PCR) and partial least-squares regression (PLSR), the use of unlabeled data, in addition to labeled data, helps stabilize the latent subspaces in the calibration step, typically leading to a lower prediction error. A non- ...

Wiley-Blackwell2011

Performance limits of LMS-based adaptive networks

Ali H. Sayed

In this work we analyze the mean-square performance of different strategies for adaptation over two-node least-mean-squares (LMS) networks. The results highlight some interesting properties for adaptive networks in comparison to centralized solutions. The ...

IEEE2011

Recursive Implementation of the Distributed Karhunen-Loeve Transform

Michael Christoph Gastpar

In the distributed linear source coding problem, a set of distributed sensors observe subsets of a data vector with noise, and provide the fusion center linearly encoded data. The goal is to determine the encoding matrix of each sensor such that the fusion ...

2010