Wyszukiwarka
dr hab. inż. Tomasz Talaśka
Zatrudnienie
- Profesor uczelni w Katedra Systemów Decyzyjnych i Robotyki
Publikacje
Filtry
wszystkich: 5
Katalog Publikacji
Rok 2024
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C-reactive protein (CRP) evaluation in human urine using optical sensor supported by machine learning
PublikacjaThe rapid and sensitive indicator of inflammation in the human body is C-Reactive Protein (CRP). Determination of CRP level is important in medical diagnostics because, depending on that factor, it may indicate, e.g., the occurrence of inflammation of various origins, oncological, cardiovascular, bacterial or viral events. In this study, we describe an interferometric sensor able to detect the CRP level for distinguishing between...
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Modelling and simulations in time-fractional electrodynamics based on control engineering methods
PublikacjaIn this paper, control engineering methods are presented with regard to modelling and simulations of signal propagation in time-fractional (TF) electrodynamics. That is, signal propagation is simulated in electromagnetic media described by Maxwell’s equations with fractional-order constitutive relations in the time domain. We demonstrate that such equations in TF electrodynamics can be considered as a continuous-time system of...
Rok 2023
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A new deterministic PSO algorithm for real-time systems implemented on low-power devices
PublikacjaThe paper presents a novel, deterministic particle swarm optimization (PSO) algorithm, facilitating its implementation in low-power application specific integrated circuits (ASIC) realized in CMOS technology. The PSO algorithms are commonly used in a variety of optimization problems. They allow to search for a global extreme in a selected fitness function, which is used for numerical modeling of specific optimized problems. The...
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A novel hardware implemented programmable controller adapted to cooperate with AI tuning algorithms in real time systems
PublikacjaA novel, transistor level PID (proportional–integrating–derivative) controller is proposed that may be easily coupled with various AI algorithms responsible for adjusting its main factors. In our work we focus on a discrete-time digital approach, as it facilities realization a flexible and programmable structure that can be quickly re-configured depending on varying environment conditions. One of the novelties of the proposed solution...
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Fuzzy Gaussian Decision Tree
PublikacjaThe Decision Tree algorithm is one of the first machine learning algorithms developed. It is used both as a standalone model and as an ensemble of many cooperating trees like Random Forest, AdaBoost, Gradient Boosted Trees, or XGBoost. In this work, a new version of the Decision Tree was developed for classifying real-world signals using Gaussian distribution functions and a fuzzy decision process. The research was carried out...
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