Philippe Dreesen (P.)

Philippe's research focuses on system identification, tensor decompositions, signal processing, recurrence plots, and multivariate polynomials, with an emphasis on developing mathematical modeling techniques for analyzing nonlinear systems.

Google Scholar: https://scholar.google.com/citations?user=1n0KQqgAAAAJ&hl=en

• Usevich, K., Zniyed, Y., Ishteva, M., Dreesen, P., & Almeida, A. L. F. D. (2023). Tensor-Based Two-Layer Decoupling of Multivariate Polynomial Maps. In 2023 31st European Signal Processing Conference (EUSIPCO) (pp. 655-659). Article 10289900 The IEEE. https://doi.org/10.23919/EUSIPCO58844.2023.10289900

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• Joshi, S., Dreesen, P., Bonizzi, P., Karel, J., Peeters, R., & Boussé, M. (2024). Novel Tensor-based Singular Spectrum Decomposition. In 32nd European Signal Processing Conference, EUSIPCO 2024 - Proceedings (pp. 1327-1331). IEEE. https://doi.org/10.23919/EUSIPCO63174.2024.10715185

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• Verbeke, D., Ishteva, M., & Dreesen, P. (2023). MIMO transfer function decoupling by Loewner tensorization. IFAC-PapersOnLine, 56(2), 7300-7305. https://doi.org/10.1016/j.ifacol.2023.10.342

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• De Jonghe, J., Usevich, K., Dreesen, P., & Ishteva, M. (2023). Compressing Neural Networks with Two-Layer Decoupling. In 2023 IEEE 9th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2023 (pp. 226-230). IEEE. https://doi.org/10.1109/CAMSAP58249.2023.10403509

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• Vijayan, P., Dreesen, P., Lataire, J., & Ishteva, M. (2023). Demonstrating equivalence between PNLSS and Volterra models for some SISO block-oriented models. 25-25. Poster session presented at 2023 workshop of the European Research Network on System Identification (ERNSI), Stockholm, Sweden.

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P Dreesen, M Ishteva, J Schoukens, "Decoupling multivariate polynomials using first-order information and tensor decompositions", SIAM Journal on Matrix analysis and Applications 36 (2), 864-879, 2015.

T Falck, P Dreesen, K De Brabanter, K Pelckmans, B De Moor, "Least-squares support vector machines for the identification of Wiener–Hammerstein systems", Control Engineering Practice 20 (11), 1165-1174, 2012.

P Dreesen, K Batselier, B De Moor, "Back to the roots: Polynomial system solving, linear algebra, systems theory", IFAC Proceedings Volumes 45 (16), 1203-1208, 2012.

K De Brabanter, P Dreesen, P Karsmakers, K Pelckmans, J De Brabanter, JAK Suykens, B De Moor, "Fixed-size LS-SVM applied to the Wiener-Hammerstein benchmark", IFAC Proceedings Volumes 42 (10), 826-831, 2009.

AF Esfahani, P Dreesen, K Tiels, JP Noël, J Schoukens, "Parameter reduction in nonlinear state-space identification of hysteresis", Mechanical Systems and Signal Processing 104, 884-895, 2018.

P Dreesen, "Back to the roots: Polynomial system solving using linear algebra", PhD thesis. Faculty of Engineering Science, KU Leuven, Belgium, 2013.

P Dreesen, B De Moor, "Polynomial optimization problems are eigenvalue problems", Model-Based Control: Bridging Rigorous Theory and Advanced Technology, 49-68, 2009.

P Dreesen, M Schoukens, K Tiels, J Schoukens, "Decoupling static nonlinearities in a parallel Wiener-Hammerstein system: A first-order approach", 2015 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), Pisa, Italy, 2015.

J Decuyper, P Dreesen, J Schoukens, MC Runacres, K Tiels, "Decoupling multivariate polynomials for nonlinear state-space models", IEEE Control Systems Letters 3 (3), 745-750, 2019.

K Batselier, P Dreesen, BD Moor, "The geometry of multivariate polynomial division and elimination", SIAM Journal on Matrix Analysis and Applications 34 (1), 102-125, 2013.

K Batselier, P Dreesen, B De Moor, "On the null spaces of the Macaulay matrix", Linear Algebra and its Applications 460, 259-289, 2014.

P Dreesen, K Batselier, B De Moor, "Multidimensional realisation theory and polynomial system solving", International Journal of Control 91 (12), 2692-2704, 2018.

AF Esfahani, P Dreesen, K Tiels, JP Noël, J Schoukens, "Polynomial state-space model decoupling for the identification of hysteretic systems", IFAC-PapersOnLine 50 (1), 458-463, 2017.

K Batselier, P Dreesen, B De Moor, "A fast recursive orthogonalization scheme for the Macaulay matrix", Journal of Computational and Applied Mathematics 267, 20-32, 2014.

VK Mishra, I Markovsky, A Fazzi, P Dreesen, "Data-driven simulation for NARX systems", 2021 29th European Signal Processing Conference (EUSIPCO), 1055-1059, 2021.

K Batselier, P Dreesen, B De Moor, "The Canonical Decomposition of  and Numerical Gröbner and Border Bases", SIAM Journal on Matrix Analysis and Applications 35 (4), 1242-1264, 2014.

K Batselier, P Dreesen, B De Moor, "A geometrical approach to finding multivariate approximate LCMs and GCDs", Linear Algebra and its Applications 438 (9), 3618-3628, 2013.

K Batselier, P Dreesen, B De Moor, "Prediction error method identification is an eigenvalue problem", IFAC Proceedings Volumes 45 (16), 221-226, 2012.

K Usevich, P Dreesen, M Ishteva, "Decoupling multivariate polynomials: Interconnections between tensorizations", Journal of Computational and Applied Mathematics 363, 22-34, 2020.

P Dreesen, J De Geeter, M Ishteva, "Decoupling multivariate functions using second-order information and tensors", LVA/ICA 2018. 

For a full publication list, check Google Scholar: https://scholar.google.com/citations?user=1n0KQqgAAAAJ&hl=en