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Dynamical Systems in Neuroscience

Eugene M. Izhikevich • The MIT Press eBooks (2006)

Explains the relationship of electrophysiology, nonlinear dynamics, and the computational properties of neurons, with each concept presented in terms of both neuroscience and mathematics and illustrated using geometrical intuition. In order...

OPENALEX DOI: https://doi.org/10.7551/mitpress/2526.001.0001

Human capital and the informal economy as asymmetric drivers of the ecological footprint in Bangladesh

Md. Golam Kibria, Mahinur Begum Mimi, Ismay Jahan, Jeremy Ko et al. • Discover Sustainability (2026)

Abstract This article assesses the impact of the shadow economy on Bangladesh’s ecological footprint and how this association is influenced by the country’s level of human capital. Using annual data from 1994 to 2020, it employs both the Li...

DOAJ Open Access (DOAJ) DOI: 10.1007/s43621-026-03721-9

Introduction to artificial neural networks

Enzo Grossi, Massimo Buscema • European Journal of Gastroenterology & Hepatology (2007)

The coupling of computer science and theoretical bases such as nonlinear dynamics and chaos theory allows the creation of 'intelligent' agents, such as artificial neural networks (ANNs), able to adapt themselves dynamically to problems of h...

OPENALEX DOI: https://doi.org/10.1097/meg.0b013e3282f198a0

Validation of Infinite Impulse Response Multilayer Perceptron for Modelling Nuclear Dynamics

F. Cadini, E. Zio, N. Pedroni • Science and Technology of Nuclear Installations (2008)

Artificial neural networks are powerful algorithms for constructing nonlinear empirical models from operational data. Their use is becoming increasingly popular in the complex modeling tasks required by diagnostic, safety, and control appli...

DOAJ Open Access (DOAJ) DOI: 10.1155/2008/681890

Deep learning for universal linear embeddings of nonlinear dynamics

Bethany Lusch, J. Nathan Kutz, Steven L. Brunton • Nature Communications (2018)

Identifying coordinate transformations that make strongly nonlinear dynamics approximately linear has the potential to enable nonlinear prediction, estimation, and control using linear theory. The Koopman operator is a leading data-driven e...

OPENALEX cc-by DOI: https://doi.org/10.1038/s41467-018-07210-0 PMC: 6251871