Results 271 to 280 of about 1,765,864 (313)
Integrating Image Segmentation and Deep Learning to Improve Radio Frequency Propagation Models
International Journal of Satellite Communications and Networking, EarlyView.ABSTRACT This paper proposes a multi‐sensor approach to improve radio frequency (RF) propagation models, which play a key role in the rapidly expanding field of connected vehicle technology. Focusing on the 1‐ to 20‐GHz frequency range, which is critical for both satellite‐to‐vehicle and base station‐to‐vehicle communications, our study introduces a ...
Jonathan Israel +2 more
wiley +1 more source
Sustainable Development, EarlyView.ABSTRACT Energy dependence poses significant risks for economic development, particularly in regions that rely heavily on imported fossil fuels. This paper examines how energy dependence and energy import diversification influence economic development across 27 European Union countries between 2000 and 2022. Using IV‐GMM and panel quantile regressions,
Mehmet Pinar
wiley +1 more source
Markov chain-based impact analysis of the pandemic Covid-19 outbreak on global primary energy consumption mix. [PDF]
Sci RepAhmad H +5 more
europepmc +1 more source
Gradient boosting: A computationally efficient alternative to Markov chain Monte Carlo sampling for fitting large Bayesian spatio-temporal binomial regression models. [PDF]
Infect Dis ModelHuang R +5 more
europepmc +1 more source
Author Correction: Markov chain-based impact analysis of the pandemic Covid-19 outbreak on global primary energy consumption mix. [PDF]
Sci RepAhmad H +5 more
europepmc +1 more source
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IEEE Trans. Inf. Theory, 1984
Summary: The Markov chain that has maximum entropy for given first and second moments is determined. The solution provides a discrete analog to the continuous Gauss-Markov process.
Jørn Justesen, Tom Høholdt
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Summary: The Markov chain that has maximum entropy for given first and second moments is determined. The solution provides a discrete analog to the continuous Gauss-Markov process.
Jørn Justesen, Tom Høholdt
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2005
Abstract Useful models of the real world have to satisfy two conflicting requirements: they must be sufficiently complicated to describe complex systems, but they must also be sufficiently simple for us to analyse them. This chapter introduces Markov chains, which have successfully modelled a huge range of scientific and social phenomena,
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Abstract Useful models of the real world have to satisfy two conflicting requirements: they must be sufficiently complicated to describe complex systems, but they must also be sufficiently simple for us to analyse them. This chapter introduces Markov chains, which have successfully modelled a huge range of scientific and social phenomena,
openaire +1 more source
1997
Markov chains are central to the understanding of random processes. This is not only because they pervade the applications of random processes, but also because one can calculate explicitly many quantities of interest. This textbook, aimed at advanced undergraduate or MSc students with some background in basic probability theory, focuses on Markov ...
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Markov chains are central to the understanding of random processes. This is not only because they pervade the applications of random processes, but also because one can calculate explicitly many quantities of interest. This textbook, aimed at advanced undergraduate or MSc students with some background in basic probability theory, focuses on Markov ...
openaire +1 more source