Frank C. Hoppensteadt is affiliated with the Courant Institute of Mathematical Sciences in the United States. Their research spans several fields, demonstrating interdisciplinary expertise across neuroscience, computer science, and engineering.
Their work addresses key topics in neural dynamics and brain function, neural networks and reservoir computing, and advanced memory and neural computing. These areas reflect a focus on understanding complex computational processes in the brain and applying these insights to artificial intelligence and engineering systems.
Hoppensteadt has contributed to the scientific community with publications that include the paper titled A Frequency-Phase Potential for a Forced STNO Network: an Example of Evoked Memory, published in 2020 in arXiv (Cornell University). This paper is associated with themes in cognitive neuroscience, artificial intelligence, and electrical and electronic engineering.
Frank C. Hoppensteadt;Eugene M. Izhikevich
Takashi Nishikawa;Adilson E. Motter;Ying Cheng Lai;Frank C. Hoppensteadt
Frank Charles Hoppensteadt
J. P. Keener;F. C. Hoppensteadt;J. Rinzel
Frank Hoppensteadt
Frank C. Hoppensteadt;Eugene Izhikevich
F. C. Hoppensteadt
Frank C. Hoppensteadt
Frank Hoppensteadt
F.C. Hoppensteadt;E.M. Izhikevich
M. Levi;F. C. Hoppensteadt;W. L. Miranker
Frank C. Hoppensteadt
Frank C. Hoppensteadt;Eugene M. Izhikevich
F. C. Hoppensteadt
Anatoli V. Skorokhod;Frank C. Hoppensteadt;Habib Salehi
Frank Hoppensteadt
Joseph E Flaherty;Joseph E Flaherty;F C Hoppensteadt;F C Hoppensteadt;F C Hoppensteadt
Eugene M. Izhikevich;Eugene M. Izhikevich;Frank C. Hoppensteadt;Frank C. Hoppensteadt
Hoppensteadt;Charles S Peskin
Hoppensteadt;Charles S Peskin
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