Quantitative biomechanical models can identify control parameters that are used during
movements, and movement parameters that are encoded by premotor neurons. We fit a …

We show how to characterize a strange attractor by a set of integers. These are extracted
from the chaotic time-series data by first reconstructing the low-period orbits and then …

We present a model of sound production in a songbird’s vocal organ and find that much of
the complexity of the song of the canary (Serinus canaria) can be produced from simple time …

We have applied topological methods to analyze chaotic time series data from the Belousov-Zhabotinskii
reaction. First, the periodic orbits shadowed by the data set were identified. …

… Part of this book was written during a period in which Gabriel Mindlin enjoyed the hospitality
of the Institute for Nonlinear Science, University of California at San Diego. Heide Doss-…

We present results of different approaches to model the evolution of the COVID-19 epidemic
in Argentina, with a special focus on the megacity conformed by the city of Buenos Aires …

Birdsong, a rich and complex behavior, is a stellar model to understand a variety of biological
problems, from motor control to learning. It also enables us to study how behavior emerges …

We present a dynamical model of the processes involved in birdsong production, relating
qualitatively its parameters with biological ones. In this way, we intend to unify the activity …

Time series forecasting has historically been a key research problem in science and engineering.
In recent years, machine learning algorithms have proven to be a very successful data-…

The physiology of sound production in suboscines is poorly investigated. Suboscines are
thought to develop song innately unlike the closely related oscines. Comparing phonatory …