Search Results for author: Ion Matei

Found 8 papers, 0 papers with code

AI Enhanced Control Engineering Methods

no code implementations8 Jun 2023 Ion Matei, Raj Minhas, Johan de Kleer, Alexander Felman

In this paper, we explore how AI tools can be useful in control applications.

Model Predictive Control

A Quantum Algorithm for Computing All Diagnoses of a Switching Circuit

no code implementations8 Sep 2022 Alexander Feldman, Johan de Kleer, Ion Matei

In this paper we provide a novel approach for computing diagnosis of switching circuits with gate-based quantum computers.

System Resilience through Health Monitoring and Reconfiguration

no code implementations30 Aug 2022 Ion Matei, Wiktor Piotrowski, Alexandre Perez, Johan de Kleer, Jorge Tierno, Wendy Mungovan, Vance Turnewitsch

The framework is based on a physics-based digital twin model and three modules tasked with real-time fault diagnosis, prognostics and reconfiguration.

Improving the Efficiency of Gradient Descent Algorithms Applied to Optimization Problems with Dynamical Constraints

no code implementations26 Aug 2022 Ion Matei, Maksym Zhenirovskyy, Johan de Kleer, John Maxwell

In our second algorithm, we use an ODE solver to reset the ODE solution, but no direct are adjoint sensitivity analysis methods are used.

Computational Efficiency

Hybrid modeling: Applications in real-time diagnosis

no code implementations4 Mar 2020 Ion Matei, Johan de Kleer, Alexander Feldman, Rahul Rai, Souma Chowdhury

In this paper, we outline a novel hybrid modeling approach that combines machine learning inspired models and physics-based models to generate reduced-order models from high fidelity models.

BIG-bench Machine Learning

Design Space Exploration as Quantified Satisfaction

no code implementations7 May 2019 Alexander Feldman, Johan de Kleer, Ion Matei

We apply our method to the design of Boolean systems and discover new and more optimal classical digital and quantum circuits for common arithmetic functions such as addition and multiplication.

Combinatorial Optimization

Recognizing Abnormal Heart Sounds Using Deep Learning

no code implementations14 Jul 2017 Jonathan Rubin, Rui Abreu, Anurag Ganguli, Saigopal Nelaturi, Ion Matei, Kumar Sricharan

The work presented here applies deep learning to the task of automated cardiac auscultation, i. e. recognizing abnormalities in heart sounds.

Sound Classification Specificity

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