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We present a new, scalable alternative to the structured singular value, which we call v, provide a convex upper bound, study their properties and compare them to l1 robust control. The analysis relies on a novel result on the relationship between robust control of dynamical systems and non-negative constant matrices.
In this paper we investigate simultaneous radial distortion calibration and motion estimation for vehicles travelling parallel to planar surfaces. This is done by estimating the inter-image homography between two poses, as well as the distortion parameter. Radial distortion correction is often performed as a pre-calibration step; however, accurately estimating the distortion profile without specia
We study the realizability and strong satisfiability problems for SAFETY LTL, a syntactic fragment of Linear Temporal Logic ([Formula presented]) capturing safe formulas. While it is well-known that realizability for this fragment lies in [Formula presented], the best-known lower bound is [Formula presented]-hardness. Surprisingly, closing this gap has proven an elusive task. Previous works have c
Despite the successes in the use of artificial intelligence systems for image analysis, in certain critical applications, the final decision-making should remain with the human operator. To facilitate the working conditions of an unmanned aerial vehicle (UAV) pilot during prolonged missions, an auxiliary narrow-angle video camera is installed on board the UAV. This camera can be positioned indepen
We prove the first hardness results against efficient proof search by quantum algorithms. We show that under Learning with Errors (LWE), the standard lattice-based cryptographic assumption, no quantum algorithm can weakly automate TC0-Frege. This extends the line of results of Krajíček and Pudlák (Information and Computation, 1998), Bonet, Pitassi, and Raz (FOCS, 1997), and Bonet, Domingo, Gavaldà
Ensuring availability is a critical requirement for the Internet of Things (IoT). CIDER, a recovery architecture, and its follow-up scheme, Lazarus, are solutions to address this issue. CIDER introduced a new hardware module, the Authenticated Watchdog Timer (AWDT), to keep IoT devices running in normal mode as long as trusted authenticated tickets are received from a hub. If valid tickets are not
Network Data Analytics Function (NWDAF) is a key component in 5G networks, introduced by 3G Partnership Project (3GPP) standards, that leverages machine learning to optimize network performance. The 3GPP standards mandate that mobile network operators should retrain NWDAF models to maintain accuracy. However, the presence of adversarial user equipment (UE) can introduce corrupted data points durin
This article considers state estimation of rigid-body dynamics where the positions q are available to measurement but where the angular velocities ̇or accelerations are not available to measurement. Using a stability-oriented approach to model-based design of state estimation for Euler–Lagrange systems and rigid-body dynamics, state estimation based on position measurement is shown to guarantee se
Pseudo-Random Injections (PRIs) have been used in several applications in symmetric-key cryptography, such as in the idealization of Authenticated Encryption with Associated Data (AEAD) schemes, building robust AEAD, and, recently, in converting a committing AEAD scheme into a succinctly committing AEAD scheme. In Crypto 2024, Bellare and Hoang showed that if an AEAD scheme is already committing
Automated cryptanalysis has seen a lot of attraction and success in the past decade, leading to new distinguishers or key-recovery attacks against various ciphers. We argue that the improved efficiency and usability of these new tools have been undervalued, especially for design processes. In this article, we break for the first time the classical iterative design paradigm for symmetric-key primit
There is a large variability between individuals in the response to anesthetic drugs, that seriously limits the achievable performance of closed-loop controlled drug dosing. Full individualization of patient models based on early clinical response data has been suggested as a means to improve performance with maintained robustness (safety). We use estimation theoretic analysis and realization theo
Numerous modelling efforts have attempted to characterize the effects of different non-pharmaceutical interventions (NPIs) on the Covid-19 spread. Arguably the most famous is one published in Nature by an Imperial College group. A slight variation of it was later published in Science by a group of Oxford researchers. Both publications are based on hierarchical Bayesian modelling that aims to expla
Novel methods for the inference of radiation intensityfunctions defined over known surfaces are proposed, intendedfor use in surveying applications with mobile spectrometers.Previous approaches, based on the maximum likelihoodexpectation maximization (ML-EM) framework with Poissonlikelihoods, are extended to better handle spatially continuousintensity statistics using ideas from Gaussian filtering
This article addresses the distributed cooperative control design for a class of sampled-data teleoperation systems with multiple slave mobile manipulators grasping an object in the presence of communication bandwidth limitation and time delays. Discrete-time information transmission with time-varying delays is assumed, and the Round-Robin (RR) scheduling protocol is used to regulate the data tran
A 32 Kb dual-port low-voltage SRAM in 28 nm FD-SOI, featuring foundry supplied high-density 6T bitcells, is presented. Dual-port configurability is realized by a unique dual-rail architecture, utilizing boost techniques that guarantee reliable operation in low-voltage. The area cost of the array is 62% lower, compared to widely used 8T two-port or dual-port SRAM arrays. The SRAM reliably operates
ControlSystems.jl enables the powerful features of the Julia language to be leveraged for control design and analysis.The toolbox provides types for state-space, transfer-function, and time-delay models, together with algorithms for design and analysis.Julia's mathematically-oriented syntax is convenient for implementing control algorithms, and its just-in-time compilation gives performance on par
AI solutions seem to appear in any and all application domains. As AI becomes more pervasive, the importance of quality assurance increases. Unfortunately, there is no consensus on what artificial intelligence means and interpretations range from simple statistical analysis to sentient humanoid robots. On top of that, quality is a notoriously hard concept to pinpoint. What does this mean for AI qu
In inverse optimal control, an optimal controller is synthesized with respect to a meaningful, a posteriori defined, cost functional. Our work illustrates the usefulness of this approach in the control of converter-based power systems and networked systems in general, and thereby in finding controllers with topological structure and known optimality properties. In particular, we design an inverse
Low-rank inducing unitarily invariant norms have been introduced to convexify problems with a low-rank/sparsity constraint. The most well-known member of this family is the so-called nuclear norm. To solve optimization problems involving such norms with proximal splitting methods, efficient ways of evaluating the proximal mapping of the low-rank inducing norms are needed. This is known for the nuc
