Zobrazeno 1 - 10
of 2 119
pro vyhledávání: '"A, Karbowski"'
Traffic microsimulation is a crucial tool that uses microscopic traffic models, such as car-following and lane-change models, to simulate the trajectories of individual agents. This digital platform allows for the assessment of the impact of emerging
Externí odkaz:
http://arxiv.org/abs/2409.19090
Autor:
Karbowski, Jan
Publikováno v:
Entropy 26, 779 (2024)
This paper provides a perspective on applying the concepts of information thermodynamics, developed recently in non-equilibrium statistical physics, to problems in theoretical neuroscience. Historically, information and energy in neuroscience have be
Externí odkaz:
http://arxiv.org/abs/2409.17599
Autor:
Karbowski, Jan, Urban, Paulina
Publikováno v:
Neural Computation 36: 271-311 (2024)
We investigate a mutual relationship between information and energy during early phase of LTP induction and maintenance in a large-scale system of mutually coupled dendritic spines, with discrete internal states and probabilistic dynamics, within the
Externí odkaz:
http://arxiv.org/abs/2404.14123
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-15 (2024)
Abstract This paper presents a comprehensive analysis of the impact of adaptive cruise control on energy consumption in real-world driving conditions based on a natural experiment: a large-scale observational dataset of driving data from a diverse fl
Externí odkaz:
https://doaj.org/article/305de39e41f74685b298ece3ae0a9309
Autor:
Karbowski, Jan
Publikováno v:
Physical Review E 109, 054126 (2024)
Statistical divergences are important tools in data analysis, information theory, and statistical physics, and there exist well known inequalities on their bounds. However, in many circumstances involving temporal evolution, one needs limitations on
Externí odkaz:
http://arxiv.org/abs/2308.05597
Autor:
Chwiłka, Maurycy, Karbowski, Jan
Publikováno v:
Phys. Rev. E 109, 014117 (2024)
Networks with stochastic variables described by heavy tailed lognormal distribution are ubiquitous in nature, and hence they deserve an exact information-theoretic characterization. We derive analytical formulas for mutual information between element
Externí odkaz:
http://arxiv.org/abs/2307.00017
Connected and automated vehicles (CAVs) can plan and actuate control that explicitly considers performance, system safety, and actuation constraints in a manner more efficient than their human-driven counterparts. In particular, eco-driving is enable
Externí odkaz:
http://arxiv.org/abs/2211.09658
Publikováno v:
IEEE Access, Vol 12, Pp 148893-148903 (2024)
The energy efficiency of autonomous vehicles can be improved by selecting an optimized speed profile. Energy savings can be maximized by performing control optimization with knowledge of the powertrain characteristics and future driving conditions. P
Externí odkaz:
https://doaj.org/article/6d5c14d207894583addcbe9fbb488288
Generating realistic vehicle speed trajectories is a crucial component in evaluating vehicle fuel economy and in predictive control of self-driving cars. Traditional generative models rely on Markov chain methods and can produce accurate synthetic tr
Externí odkaz:
http://arxiv.org/abs/2112.08361
Autor:
Jan Karbowski, Paulina Urban
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-29 (2023)
Abstract Many experiments suggest that long-term information associated with neuronal memory resides collectively in dendritic spines. However, spines can have a limited size due to metabolic and neuroanatomical constraints, which should effectively
Externí odkaz:
https://doaj.org/article/53ba6585ee06473b9978755756d5f73a