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A robust scheme for cellular power control

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Optimal Conditionally Unbiased Bounded-Influence Inference in Dynamic Location and Scale Models

Loriano Mancini, Fabio Trojani

This paper studies the local robustness of estimators and tests for the conditional location and scale parameters in a strictly stationary time series model. We first derive optimal bounded-influence estimators for such settings under a conditionally Gauss ...

2005

Robust Predictive Control Based on Neighboring Extremals

Dominique Bonvin, Sébastien Gros

The performance of predictive controller is typically poor when the true plant evolution deviates significantly from that predicted by the model. A robust approach that considers model uncertainty explicitly is then needed. However, it is often difficult t ...

2004

General state-space models

Thomas Gsponer

In time series analysis state-space models provide a wide and flexible class. The basic idea is to describe an unobservable phenomenon of interest on the basis of noisy data. The first constituent of such a model is the so-called state equation, which char ...

EPFL2004

Adapted Generative Models For Face Verification

Samy Bengio

It has been shown previously that systems based on local features and relatively complex generative models, namely 1D Hidden Markov Models (HMMs) and pseudo-2D HMMs, are suitable for face recognition (here we mean both identification and verification). Rec ...

IDIAP2003

The Scrambled Net Filter

Thomas Gsponer

The standard Kalman filter is a powerful and widely used tool to perform prediction, filtering and smoothing in the fields of linear Gaussian state-space models. In its standard setting it has a simple recursive form which implies high computational effici ...

2002

The Scrambled Net Filter

Thomas Gsponer

2002

Comparison of robust estimation and Kalman filtering applied to fingertip tracking in human-machine interfaces

Ali H. Sayed

This paper studies the application of robust state-space estimation with uncertain models to tracking problems in human-machine interfaces. The need for robust methods arises from the desire to control the influence of uncertain environmental conditions on ...

2001

Design of robust filters with improved robustness margins via parameter scaling

Ali H. Sayed

The paper describes a procedure for improving the robustness margins of robust filters via parameter scaling. The scaling parameter is chosen as the square-root factor of the inverse of a positive-definite solution to certain matrix inequalities. This choi ...

2001

A time-domain feedback analysis of filtered-error adaptive gradient algorithms

Ali H. Sayed

This paper provides a time-domain feedback analysis of gradient-based adaptive schemes. A key emphasis is on the robustness performance of the adaptive filters in the presence of disturbances and modeling uncertainties (along the lines of H/sup /spl infin/ ...

Institute of Electrical and Electronics Engineers1996

A robustness analysis of Gauss-Newton recursive methods

Ali H. Sayed

We provide a time-domain robustness analysis of Gauss-Newton recursive methods that are often employed in identification and control. Several free parameters are included in the filter description while combining the covariance update and the weight-vector ...

1995