TÜBİTAK
104T133
In this work, we benefit from hybrid systems that are advantageous because of their
analytical and computational usefulness in the case of inferential modeling. In fact,
many biological and physiological systems exhibit historical responses such that the
system and its responses depend on the whole history rather than a combination
of historical events. In this work, we use and improve hybrid systems with memory
(HSM) in the subclass of piecewise linear differential equations. We also include
stochastic calculus to our model to exhibit uncertainties and random perturbations
clearly, and we call this model stochastic hybrid systems with memory (SHSM).
Finally, we choose tumor-immune system data from the literature and show that
the model is capable to model history dependent behavior.
hybrid systems functional differential equations pattern memorization multistationarity regulatory dynamical systems
104T133
Primary Language | English |
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Subjects | Mathematical Sciences |
Journal Section | Articles |
Authors | |
Project Number | 104T133 |
Publication Date | March 31, 2021 |
Published in Issue | Year 2021 Volume: 5 Issue: 1 |