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Modelling is an essential procedure in analyzing and controlling a given logical dynamic system (LDS). It has been proved that deterministic LDS can be modeled as a linear-like system using algebraic state space representation. However, due…

Optimization and Control · Mathematics 2022-03-04 Changxi Li , Jun-e Feng , Daizhan Cheng , Xiao Zhang

By design, quasi delay-insensitive (QDI) circuits exhibit higher resilience against timing variations as compared to their synchronous counterparts. Since computation in QDI circuits is event-based rather than clock-triggered, spurious…

Hardware Architecture · Computer Science 2023-07-07 Raghda El Shehaby , Matthias Függer , Andreas Steininger

Balancing the workload of sophisticated simulations is inherently difficult, since we have to balance both computational workload and memory footprint over meshes that can change any time or yield unpredictable cost per mesh entity, while…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-08-04 Philipp Samfass , Tobias Weinzierl , Dominic E. Charrier , Michael Bader

In this note, a novel methodology that can extract a number of analysis results for linear time-invariant systems (LTI) given only a single trajectory of the considered system is proposed. The superiority of the proposed technique relies on…

Systems and Control · Electrical Eng. & Systems 2021-09-22 Hassan Abdelraouf , Fahad Albalawi , Eric Feron

In biological and engineering systems, structure, function and dynamics are highly coupled. Such interactions can be naturally and compactly captured via tensor based state space dynamic representations. However, such representations are…

Optimization and Control · Mathematics 2019-12-30 Can Chen , Amit Surana , Anthony Bloch , Indika Rajapakse

Understanding the dynamics of time series data typically requires identifying the unique latent factors for data generation, \textit{a.k.a.}, latent processes identification. Driven by the independent assumption, existing works have made…

Machine Learning · Computer Science 2023-05-16 Zenan Huang , Haobo Wang , Junbo Zhao , Nenggan Zheng

The Sequential Linear Quadratic (SLQ) algorithm is a continuous-time variant of the well-known Differential Dynamic Programming (DDP) technique with a Gauss-Newton Hessian approximation. This family of methods has gained popularity in the…

Robotics · Computer Science 2021-03-29 Jean-Pierre Sleiman , Farbod Farshidian , Marco Hutter

Dynamical system (DS)-based learning from demonstration (LfD) is a powerful tool for generating motion plans in the operation (`task') space of robotic systems. However, the realization of the generated motion plans is often compromised by…

Robotics · Computer Science 2025-11-14 Eshika Pathak , Ahmed Aboudonia , Sandeep Banik , Naira Hovakimyan

The Map-Reduce computing framework rose to prominence with datasets of such size that dozens of machines on a single cluster were needed for individual jobs. As datasets approach the exabyte scale, a single job may need distributed…

Data Structures and Algorithms · Computer Science 2016-10-31 Riley Murray , Samir Khuller , Megan Chao

This paper considers the problem of real-time mode scheduling in linear time-varying switched systems subject to a quadratic cost functional. The execution time of hybrid control algorithms is often prohibitive for real-time applications…

Optimization and Control · Mathematics 2017-09-04 Anastasia Mavrommati , Jarvis A. Schultz , Todd D. Murphey

Scheduling multiple products with limited resources and varying demands remain a critical challenge for many industries. This work presents mixed integer programs (MIPs) that solve the Economic Lot Sizing Problem (ELSP) and other Dynamic…

Optimization and Control · Mathematics 2020-04-07 Wolfgang Garn

In this paper, we propose an LMI-based approach to analyze input-output properties of coupled linear PDE systems. This work expands on a newly developed state-space theory for coupled PDEs and extends the positive-real and bounded-real…

Optimization and Control · Mathematics 2020-05-01 Sachin Shivakumar , Matthew M. Peet

Linear algebra algorithms are used widely in a variety of domains, e.g machine learning, numerical physics and video games graphics. For all these applications, loop-level parallelism is required to achieve high performance. However,…

Machine Learning · Computer Science 2020-01-24 G. Laberge , S. Shirzad , P. Diehl , H. Kaiser , S. Prudhomme , A. Lemoine

This study proposes LiP-LLM: integrating linear programming and dependency graph with large language models (LLMs) for multi-robot task planning. In order for multiple robots to perform tasks more efficiently, it is necessary to manage the…

Robotics · Computer Science 2024-10-29 Kazuma Obata , Tatsuya Aoki , Takato Horii , Tadahiro Taniguchi , Takayuki Nagai

The paper aims at the development of an apparatus for analysis and construction of near optimal solutions of singularly perturbed (SP) optimal controls problems (that is, problems of optimal control of SP systems) considered on the infinite…

Optimization and Control · Mathematics 2014-08-20 Vladimir Gaitsgory , Sergei Rossomakhine

We introduce Parametric Linear Dynamic Logic (PLDL), which extends Linear Dynamic Logic (LDL) by temporal operators equipped with parameters that bound their scope. LDL was proposed as an extension of Linear Temporal Logic (LTL) that is…

Logic in Computer Science · Computer Science 2014-08-27 Peter Faymonville , Martin Zimmermann

In this paper, we propose a stochastic scheduling strategy for estimating the states of N discrete-time linear time invariant (DTLTI) dynamic systems, where only one system can be observed by the sensor at each time instant due to practical…

Optimization and Control · Mathematics 2015-06-23 Chong Li , Nicola Elia

This paper considers the problem of linear time-invariant (LTI) system identification using input/output data. Recent work has provided non-asymptotic results on partially observed LTI system identification using a single trajectory but is…

Optimization and Control · Mathematics 2021-11-23 Yang Zheng , Na Li

We propose a continuous-time formulation of persistent contrastive divergence (PCD) for maximum likelihood estimation (MLE) of unnormalised densities. Our approach expresses PCD as a coupled, multiscale system of stochastic differential…

Machine Learning · Statistics 2025-10-03 Paul Felix Valsecchi Oliva , O. Deniz Akyildiz , Andrew Duncan

The problem of distributing the workload on a parallel computer to minimize the overall runtime is known as Multiprocessor Scheduling Problem. It is NP-hard, but like many other NP-hard problems, the average hardness of random instances…

Disordered Systems and Neural Networks · Physics 2016-08-19 Heiko Bauke , Stephan Mertens , Andreas Engel
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