Sunday, September 18, 2022, 14:00
- 16:00
Building 1, Room 4214
Contact Person
Pulse-shaped signal characterization is a fundamental problem in signal processing. One recently developed tool available to analyze non-stationary pulse-shaped waveforms with a suitable peak reconstruction is semiclassical signal analysis (SCSA). SCSA is a signal representation method that decomposes a real positive signal y(t) into a set of squared eigenfunctions through the discrete spectrum of the Schrödinger operator which is of particular interest. Beginning with an introduction to the young method, this dissertation discusses the relevant properties of SCSA and how they are utilized in signal denoising and biomedical application. Based on this, different frameworks and methodologies are proposed to leverage the advantages of the SCSA, especially in the pulse-shaped signal analysis field.
Tuesday, April 26, 2022, 14:00
- 16:00; Building 1, Level 4, Room 4318
Cardiovascular diseases (CVDs) remain the leading cause of death worldwide. Patients at risk of evolving CVDs are assessed by evaluating a risk factor-based score that incorporates different bio-markers ranging from age and sex to arterial stiffness (AS).
Thursday, December 23, 2021, 16:00
- 18:00
Optical Wireless Communication (OWC) offers many benefits over established radio frequency-based communication links. In particular, high beam directivity generates efficient power usage and high-speed data services. Moreover, due to its ease of deployment, high transmission security, license-free operation, and insensitivity to interference, the OWC link is becoming an attractive solution for the next generation of communication systems.
Wednesday, October 14, 2020, 16:00
- 17:00
Digital health solutions improve healthcare services and help achieve sustainable and higher standards of health and well-being. These solutions are mainly based on Digital Signal Processing (DSP) to record, interpret, and diagnose bio-signals such as Electrocardiogram (ECG) or Magnetoencephalography (MEG). In my thesis, a novel signal/image post-processing algorithm is proposed based on the Semi-Classical Signal Analysis method (SCSA) to enhance biomedical data quality. In addition, new feature extraction algorithms are proposed, based on the SCSA and the new Quantization-based Position Weight Matrix (QuPWM), which opens new tracks toward smart biomedical diagnosis and decision-making assistance in different fields such as predicting true Poly(A) regions in a DNA sequence, multiple hand gesture prediction.
Thursday, November 21, 2019, 12:00
- 13:00
Building 9, Level 2, Hall 1, Room 2322
I will present an overview of our activities around estimation problems for partial and fractional differential equations. I will present the methods and the algorithms we develop for the state, source and parameters estimation and illustrate the results with some simulations and real applications.
Sunday, April 28, 2019, 09:30
- 10:30
B3 L5 Room 5209
Contact Person
Model Predictive Control (MPC) is an d advanced control strategy widely used in the process industries and beyond. Therefore, industry is interested in the developments of MPC formulations that can enhance safety, reliability, and economic profitability of chemical processes. Motivated by these considerations, the first part of this talk focuses on the development of methods for integrating process operational safety and process economics within model predictive control system designs.
Thursday, April 18, 2019, 12:00
- 13:00
B9 L2 Hall 1
We will present some new methods for source and parameters estimation for partial and fractional differential equations and illustrate the results with some simulations and real applications.