Pawel Wachel

Orcid: 0000-0002-7353-2310

According to our database1, Pawel Wachel authored at least 26 papers between 2007 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Decentralized diffusion-based learning under non-parametric limited prior knowledge.
Eur. J. Control, January, 2024

2023
A Dual Averaging Algorithm for Online Modeling of Infinite Memory Nonlinear Systems.
IEEE Trans. Autom. Control., September, 2023

Learning low-dimensional separable decompositions of MIMO non-linear systems.
Int. J. Control, April, 2023

Frequency-Supported Neural Networks for Nonlinear Dynamical System Identification.
CoRR, 2023

A Computationally Lightweight Safe Learning Algorithm.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022
On State-Space Representations of General Discrete-Time Dynamical Systems.
IEEE Trans. Autom. Control., 2022

2021
Identification of Wiener-Hammerstein systems by ℓ1-constrained Volterra series.
Eur. J. Control, 2021

Mimicking Learning for 1-NN Classifiers.
Proceedings of the Computational Science - ICCS 2021, 2021

Low-Dimensional Decompositions for Nonlinear Finite Impulse Response Modeling.
Proceedings of the Computational Science - ICCS 2021, 2021

2019
Assessment of Baroreflex Sensitivity Using Time-Frequency Analysis during Postural Change and Hypercapnia.
Comput. Math. Methods Medicine, 2019

Modeling of switching-mode nonlinear system by exponentially weighted aggregation.
Proceedings of the 24th International Conference on Methods and Models in Automation and Robotics, 2019

2018
Nonlinear system modeling based on constrained Volterra series estimates.
CoRR, 2018

2017
Wiener system modelling by exponentially weighted aggregation.
Int. J. Control, 2017

Kernel-based identification of Wiener-Hammerstein system.
Autom., 2017

Exponentially weighted aggregation of models for Wiener-Hammerstein system modelling.
Proceedings of the 22nd International Conference on Methods and Models in Automation and Robotics, 2017

Multistage identification of Wiener-Hammerstein system.
Proceedings of the Trends in Advanced Intelligent Control, Optimization and Automation - Proceedings of KKA 2017, 2017

2016
Convex aggregative modelling of infinite memory nonlinear systems.
Int. J. Control, 2016

Aggregative modeling of Wiener systems.
Proceedings of the 21st International Conference on Methods and Models in Automation and Robotics, 2016

A stochastic approach to contrast detection autofocusing. A 2D case analysis.
Proceedings of the 21st International Conference on Methods and Models in Automation and Robotics, 2016

2015
Aggregative Modeling of Nonlinear Systems.
IEEE Signal Process. Lett., 2015

Complexity of cerebral blood flow velocity and arterial blood pressure in subarachnoid hemorrhage using time-frequency analysis.
Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2015

2013
A simple scheme for semi-recursive identification of Hammerstein system nonlinearity by Haar wavelets.
Int. J. Appl. Math. Comput. Sci., 2013

Application of stochastic counterpart optimization to contrast-detection autofocusing.
Proceedings of the International Conference on Advances in Computing, 2013

Empirical Recovery of Input Nonlinearity in Distributed Element Models.
Proceedings of the 11th IFAC International Workshop on Adaptation and Learning in Control and Signal Processing, 2013

Model Selection of Hammerstein System Nonlinearity under Heavy Noise.
Proceedings of the 11th IFAC International Workshop on Adaptation and Learning in Control and Signal Processing, 2013

2007
On Nonparametric Identification of Wiener Systems.
IEEE Trans. Signal Process., 2007


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