Zobrazeno 1 - 10
of 2 030
pro vyhledávání: '"Johann, H."'
Autor:
Abella, David, Martínez, Johann H., Mazzoli, Mattia, Corre, Thibault Le, Migozzi, Julien, Alonso-Paulí, Eduard, Crespí-Cladera, Rafel, Louail, Thomas, Ramasco, José J.
The real estate market shows an inherent connection to space. Real estate agencies unevenly operate and specialize across space, price and type of properties, thereby segmenting the market into submarkets. We introduce here a methodology based on mul
Externí odkaz:
http://arxiv.org/abs/2405.08398
During the last years, statistical physics has received an increasing attention as a framework for the analysis of real complex systems; yet, this is less clear in the case of international political events, partly due to the complexity in securing r
Externí odkaz:
http://arxiv.org/abs/2203.07403
Autor:
Mir Ahsan Ali, Katharina Lischka, Stephanie J. Preuss, Chintan A. Trivedi, Johann H. Bollmann
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-18 (2023)
Abstract In motor control, the brain not only sends motor commands to the periphery, but also generates concurrent internal signals known as corollary discharge (CD) that influence sensory information processing around the time of movement. CD signal
Externí odkaz:
https://doaj.org/article/2a7d3899e8194499a1fa8afb89d79578
Countries globally trade with tons of waste materials every year, some of which are highly hazardous. This trade admits a network representation of the world-wide waste web, with countries as vertices and flows as directed weighted edges. Here we inv
Externí odkaz:
http://arxiv.org/abs/2104.05711
Autor:
Novillo, Álvaro, Gong, Bingnan, Martínez, Johann H., Resta, Ricardo, del Campo, Roberto López, Buldú, Javier M.
Publikováno v:
In Chaos, Solitons and Fractals: the interdisciplinary journal of Nonlinear Science, and Nonequilibrium and Complex Phenomena January 2024 178
Autor:
Chavez, Mario, Martinez, Johann H.
Although classical spectral analysis is a natural approach to characterise linear systems, it cannot describe a chaotic dynamics. Here, we propose the ordinal spectrum, a method based on a spectral transformation of symbolic sequences, to characteris
Externí odkaz:
http://arxiv.org/abs/2009.02547
We introduce a new methodology to analyze the evolution of epidemic time series, which is based on the construction of epidemic networks. First, we translate the time series into ordinal patterns containing information about local fluctuations of the
Externí odkaz:
http://arxiv.org/abs/1911.05646