Publications related to Moving horizon state estimation of large-scale constrained partitioned systems

ExG Signal Feature Selection Using Hyperdimensional Computing Encoding

David Atienza Alonso, Tomas Teijeiro Campo, Una Pale

Wearable IoT devices and novel continuous monitoring algorithms are essential components of the healthcare transition from reactive interventions focused on symptom treatment to more proactive prevention, from one-size-fits-all to personalized medicine, an ...

IEEE2022

Logic Resynthesis of Majority-Based Circuits by Top-Down Decomposition

Giovanni De Micheli, Heinz Riener, Siang-Yun Lee

Logic resynthesis is the problem of finding a dependency function to re-express a given Boolean function in terms of a given set of divisor functions. In this paper, we study logic resynthesis of majority-based circuits, which is motivated by the increasin ...

IEEE2021

Iterative distributed fault detection and isolation for linear systems based on moving horizon estimation

René Uwe Schneider, Marcello Farina

In modern engineering systems, reliability and safety can be conferred by efficient automatic monitoring and fault detection algorithms, allowing for the early identification and isolation of incipient faults. In case of large-scale and complex systems, sc ...

2020

Roundtable Panel Discussion at DAC 2019: Evolutionary Computing or Heuristic Forever?

Giovanni De Micheli, Massimiliano Di Ventra

As demands for computing have been continuously increasing, various solutions have been proposed. Some approaches deal with improving algorithms and software programs, mainly through the tuning of advanced heuristics and learning methods. Some other tackle ...

2020

The Complexity of Splitting Necklaces and Bisecting Ham Sandwiches

Aris Filos Ratsikas

We resolve the computational complexity of two problems known as NECKLACE-SPLITTING and DISCRETE HAM SANDWICH, showing that they are PPA-complete. For NECKLACE SPLITTING, this result is specific to the important special case in which two thieves share the ...

ACM2019

Super Resolution Phase Retrieval for Sparse Signals

Martin Vetterli, Juri Ranieri, Gilles Baechler, Amina Chebira, Miranda Krekovic

In a variety of fields, in particular those involving imaging and optics, we often measure signals whose phase is missing or has been irremediably distorted. Phase retrieval attempts to recover the phase information of a signal from the magnitude of its Fo ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2018

Perception-aware Receding Horizon Navigation for MAVs

Davide Scaramuzza

To reach a given destination safely and accurately, a micro aerial vehicle needs to be able to avoid obstacles and minimize its state estimation uncertainty at the same time. To achieve this goal, we propose a perception-aware receding horizon approach. In ...

2018

Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

Michaël Unser, Martin Kurt Storath

We consider

L ^{ 1 }

-TV regularization of univariate signals with values on the real line or on the unit circle. While the real data space leads to a convex optimization problem, the problem is nonconvex for circle-valued data. In this paper, we deriv ...

SIAM2016

K-Adaptability in Two-Stage Distributionally Robust Binary Programming

Daniel Kuhn, Grani Adiwena Hanasusanto, Wolfram Wiesemann

We propose to approximate two-stage distributionally robust programs with binary recourse decisions by their associated K-adaptability problems, which pre-select K candidate second-stage policies here-and-now and implement the best of these policies once t ...

Elsevier Science Bv2016

A Comment on “Computational Complexity of Stochastic Programming Problems”

Daniel Kuhn, Grani Adiwena Hanasusanto, Wolfram Wiesemann

Although stochastic programming problems were always believed to be computationally challenging, this perception has only recently received a theoretical justification by the seminal work of Dyer and Stougie (Mathematical Programming A, 106(3):423–432, 200 ...

Springer Heidelberg2016

Moving horizon state estimation of large-scale constrained partitioned systems

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ExG Signal Feature Selection Using Hyperdimensional Computing Encoding

Logic Resynthesis of Majority-Based Circuits by Top-Down Decomposition

Iterative distributed fault detection and isolation for linear systems based on moving horizon estimation

Roundtable Panel Discussion at DAC 2019: Evolutionary Computing or Heuristic Forever?

The Complexity of Splitting Necklaces and Bisecting Ham Sandwiches

Super Resolution Phase Retrieval for Sparse Signals

Perception-aware Receding Horizon Navigation for MAVs

Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

K-Adaptability in Two-Stage Distributionally Robust Binary Programming

A Comment on “Computational Complexity of Stochastic Programming Problems”

Roundtable Panel Discussion at DAC 2019: Evolutionary Computing or Heuristic Forever?

ExG Signal Feature Selection Using Hyperdimensional Computing Encoding

Iterative distributed fault detection and isolation for linear systems based on moving horizon estimation

Perception-aware Receding Horizon Navigation for MAVs

The Complexity of Splitting Necklaces and Bisecting Ham Sandwiches

Logic Resynthesis of Majority-Based Circuits by Top-Down Decomposition

K-Adaptability in Two-Stage Distributionally Robust Binary Programming

A Comment on “Computational Complexity of Stochastic Programming Problems”

Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

Super Resolution Phase Retrieval for Sparse Signals