Publications related to Best, worst and average case

Integration of a Real-Time Node for Magnetic Perturbations Signal Analysis in the Distributed Digital Control System of the TCV Tokamak

Olivier Sauter, Basil Duval, Stefano Coda, Jean-Marc Moret, Duccio Testa, Xavier Llobet, Cristian Galperti

This paper presents the integration of an acquisition and computing unit capable of acquiring and processing fast magnetic signals in real time in the control system of the tokamak a configuration variabile tokamak. All aspects of system integration and te ...

2017

Jump-Penalized Least Absolute Values Estimation of Scalar or Circle-Valued Signals

Michaël Unser, Martin Kurt Storath

We study jump-penalized estimators based on least absolute deviations which are often referred to as Potts estimators. They are estimators for a parsimonious piecewise constant representation of noisy data having a noise distribution which has heavier tail ...

Oxford University Press2017

Control-Quality Driven Design of Embedded Control Systems with Stability Guarantees

Amir Aminifar

Today, the majority of control applications in embedded systems, e.g., in the automotive domain, are implemented as software tasks on shared platforms. Ignoring implementation impacts during the design of embedded control systems results in complex timing ...

2017

Synthesizing efficient systems in probabilistic environments

Barbara Jobstmann, David Parker

We present a formalism, algorithms and tools to synthesise reactive systems that behave efficiently, i.e., which achieve an optimal trade-off between a given cost and reward model. Synthesis aims to automatically generate a program from a specification. Mo ...

Springer2016

Worst-case execution time analysis for many-core architectures with NoC

Alena Simalatsar, Stefanos Skalistis

The optimal deployment of data streaming applications onto multi-/many-core platform providing real-time guarantees requires to solve the application partitioning and placement, buffer allocation and task mapping and scheduling optimisation problem using t ...

Springer Int Publishing Ag2016

From Acoustic Room Reconstruction to SLAM

Martin Vetterli, Ivan Dokmanic

Recent works on reconstruction of room geometry from echoes assume that the geometry of the sensor array is known. In this paper, we show that such an assumption is not essential; echoes provide sufficient clues to reconstruct the room’s and the array’s ge ...

Ieee2016

SHAPE: Linear-Time Camera Pose Estimation With Quadratic Error-Decay

Martin Vetterli, Adam James Scholefield, Alireza Ghasemi

We propose a novel camera pose estimation or perspective-n-point (PnP) algorithm, based on the idea of consistency regions and half-space intersections. Our algorithm has linear time-complexity and a squared reconstruction error that decreases at least qua ...

Ieee2016

On convergence and performance certification of a continuous-time economic model predictive control scheme with time-varying performance index

Colin Neil Jones, Andrea Alessandretti

This paper addresses the design of convergence and performance certified sampled-data model predictive control (MPC) laws with a time-dependent economic performance index. More precisely, using a dissipativity property of the system, we provide a set of su ...

Pergamon-Elsevier Science Ltd2016

Learning-Based Compressive Subsampling

Volkan Cevher, Jonathan Mark Scarlett, Ilija Bogunovic, Yen-Huan Li, Luca Baldassarre, Baran Gözcü

The problem of recovering a structured signal

\mathbf{x} \in \mathbb{C}^p

from a set of dimensionality-reduced linear measurements

\mathbf{b} = \mathbf {A}\mathbf {x}

arises in a variety of applications, such as medical imaging, spectroscopy, Fourier o ...

Ieee-Inst Electrical Electronics Engineers Inc2016

Robustness of classifiers: from adversarial to random noise

Pascal Frossard, Seyed Mohsen Moosavi Dezfooli, Alhussein Fawzi

Several recent works have shown that state-of-the-art classifiers are vulnerable to worst-case (i.e., adversarial) perturbations of the datapoints. On the other hand, it has been empirically observed that these same classifiers are relatively robust to ran ...

2016

Best, worst and average case

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Integration of a Real-Time Node for Magnetic Perturbations Signal Analysis in the Distributed Digital Control System of the TCV Tokamak

Jump-Penalized Least Absolute Values Estimation of Scalar or Circle-Valued Signals

Control-Quality Driven Design of Embedded Control Systems with Stability Guarantees

Synthesizing efficient systems in probabilistic environments

Worst-case execution time analysis for many-core architectures with NoC

From Acoustic Room Reconstruction to SLAM

SHAPE: Linear-Time Camera Pose Estimation With Quadratic Error-Decay

On convergence and performance certification of a continuous-time economic model predictive control scheme with time-varying performance index

Learning-Based Compressive Subsampling

Robustness of classifiers: from adversarial to random noise

Integration of a Real-Time Node for Magnetic Perturbations Signal Analysis in the Distributed Digital Control System of the TCV Tokamak

On convergence and performance certification of a continuous-time economic model predictive control scheme with time-varying performance index

Control-Quality Driven Design of Embedded Control Systems with Stability Guarantees

Robustness of classifiers: from adversarial to random noise

SHAPE: Linear-Time Camera Pose Estimation With Quadratic Error-Decay

Jump-Penalized Least Absolute Values Estimation of Scalar or Circle-Valued Signals

Synthesizing efficient systems in probabilistic environments

Worst-case execution time analysis for many-core architectures with NoC

From Acoustic Room Reconstruction to SLAM

Learning-Based Compressive Subsampling