Special Session “Nonlinear Estimation and Modeling”

Session Chair:
Patrick Dewilde, TU Delft  (The Netherlands), TU Munich (Germany)
Session Organizer:
Jan Zarzycki, Wroclaw University of Technology (Poland)
Session Scope:

Stochastic Modeling is the art of producing an adequate reduced model for a dynamical system driven by one or more stochastic processes.
It is an essential step not only in understanding the behavior of such a system, but also in producing an essential component for `model based control’,
whereby the control law is derived from a good estimate of the system’ structure. In the case of linear (time variant or time invariant)
systems driven by a zero-mean Gaussian process, the problem of stochastic modeling has found some very elegant solutions,
depending on the kind of data available for the identification. The data could e.g., consist of correlations or partial parametrized models.
The problem becomes much more challenging in the case of non-linear systems driven by stochastic processes of general type,
and one may doubt that there would ever be a generally applicable methodology. However, there are interesting classes of systems
for which one can derive and identify adequate (reduced) models.
The session aims at reporting recent activities and new insights in the whole area of stochastic modeling in a non-conventional context.

Keynote Speakers:
  • Prof. Patrick Dewilde (TU Delft The Netherlands, TU Munich Germany)
  • Prof. Sankar Basu (National Science Foundation, Washington DC. USA)
  • Prof. John Baras (Univ. of Maryland USA, TU Munich, KTH Stockholm)
  • Prof. Karl Johansson (Royal Institute of Technology Stockholm, Sweden)

Special session on passive radar

Session Chair:
Mateusz Malanowski, Warsaw University of Technology, Warsaw, Poland

Mateusz Malanowski is an Associate Professor at the Warsaw University of Technology, Poland. His research interests are passive radar, noise radar and SAR/ISAR.

Session Scope: The session is focused on:
  • Clutter filtering
  • Target localization
  • New illuminators of opportunity
  • Multistatic operation
  • Multiband fusion
  • PCL/PET fusion
  • PCL/active radar fusion

Special session on Biomedical Image and Signal Processing and Interpretation

Session Chairs:
  1. Piotr Augustyniak, AGH University of Science and Technology, Krakow, Poland.

    Piotr Augustyniak is the head of the Department of Biocybernertics and Biomedical Engineering in AGH-UST. His scientific interests include hardware and software problems of biosignal processing, currently he is working on watermarking of electrocardiogram, eyetracking applications and data-dependent signal representation. He prototyped four acquisition and analysis systems for electrocardiography, electrooculography and electroencephalography. He published five books on electrodiagnostic signal processing, over 220 conference papers and was a reviewer and a program committee member of many international conferences.

  2. Anton Popov, National Technical University of Ukraine “Igor Sykorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine

Anton Popov is associate professor of Electronic Engineering Department of Igor Sykorsky Kyiv Polytechnic Institute, and also is AI/Deep Learning Technical Lead at Ciklum (UK). His research interests include applications of signal processing methods to the analysis and interpretation of biomedical signals and images. Currently his group is working on epileptic seizure prediction based on electroencephalograms and cardiorythmograms, techniques for quantification of cognitive workload and emotions, recognition of imaginary movements, stabilography, as well as deep learning applications to cancer and Alzheimer’s Disease diagnosis. He published 50 papers in peer-reviewed journals and more than 100 conference papers.

Session Scope: The session aims to attract original research papers focused on:
  • multimodal sensing in medicine, wearable intelligent sensors,
  • biosignal processing and interpretation,
  • medical imaging, image recognition, fusion etc.
  • medical information techniques,
  • telemedicine, sensor networks,
  • medical data archiving and transmission techniques,
  • safety issues for medical data.