dr hab. Piotr Bartłomiejczyk | Gdańsk University of Technology

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dr hab. Piotr Bartłomiejczyk

Contact:

email:
piobartl@pg.edu.pl
website:
https://mostwiedzy.pl/piotr-bartlomiejczyk,816616-1

Positions:

Associate professor

dr hab. Piotr Bartłomiejczyk

Publications:

  1. Publication

    - Colloquium Mathematicum - Year 2024

    We prove that with only one exception, all expanding Lorenz maps $f\colon[0,1]\to[0,1]$ with the derivative $f'(x)\ge\sqrt{2}$ (apart from a finite set of points) are locally eventually onto. Namely, for each such $f$ and each nonempty open interval $J\subset(0,1)$ there is $n\in\N$ such that $[0,1)\subset f^n(J)$. The mentioned exception is the map $f_0(x)=\sqrt{2}x+(2-\sqrt{2})/2 \pmod 1$. Recall that $f$ is an expanding Lorenz...

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  2. Modeling nerve cells can facilitate formulating hypotheses about their real behavior and improve understanding of their functioning. In this paper, we study a discrete neuron model introduced by Courbage et al. [Chaos 17, 043109 (2007)], where the originally piecewise linear function defining voltage dynamics is replaced by a cubic polynomial, with an additional parameter responsible for varying the slope. Showing that on a large...

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  3. Map-based neuron models are an important tool in modeling neural dynamics and sometimes can be considered as an alternative to usually computationally costlier models based on continuous or hybrid dynamical systems. However, due to their discrete nature, rigorous mathematical analysis might be challenging. We study a discrete model of neuronal dynamics introduced by Chialvo in 1995. In particular, we show that its reduced one-dimensional...

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  4. The work studies the well-known map-based model of neuronal dynamics introduced in 2007 by Courbage, Nekorkin and Vdovin, important due to various medical applications. We also review and extend some of the existing results concerning β-transformations and (expanding) Lorenz mappings. Then we apply them for deducing important properties of spike-trains generated by the CNV model and explain their implications for neuron behaviour....

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  5. Publication

    - Homology Homotopy and Applications - Year 2021

    We compare the sets of homotopy classes of gradient and proper gradient vector fields in the plane. Namely, we show that gradient and proper gradient homotopy classi cations are essentially different. We provide a complete description of the sets of homotopy classes of gradient maps from R^n to R^n and proper gradient maps from R^2 to R^2 with the Brouwer degree greater or equal to zero.

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Projects: