Input-to-State stability analysis for memristive Cohen-Grossberg-type neural 
networks with variable time delays

Zhao, Y.; Kurths, Jürgen; Duan, L.

doi:10.1016/j.chaos.2018.07.021

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Input-to-State stability analysis for memristive Cohen-Grossberg-type neural networks with variable time delays

Zhao, Y., Kurths, J., Duan, L. (2018): Input-to-State stability analysis for memristive Cohen-Grossberg-type neural networks with variable time delays. - Chaos, Solitons & Fractals, 114, 364-369.
https://doi.org/10.1016/j.chaos.2018.07.021

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Item Permalink: https://publications.pik-potsdam.de/pubman/item/item_22669 Version Permalink: https://publications.pik-potsdam.de/pubman/item/item_22669_2

Genre: Journal Article

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Creators:
Zhao, Y.¹, Author
Kurths, Jürgen², Author
Duan, L.¹, Author

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1Potsdam Institute for Climate Impact Research and Cooperation Partners, ou_persistent13
2Potsdam Institute for Climate Impact Research, ou_persistent13

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Dates: Finally published : 2018

Publication Status: Finally published

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Identifiers: DOI: 10.1016/j.chaos.2018.07.021
PIKDOMAIN: Transdisciplinary Concepts & Methods - Research Domain IV
eDoc: 8223
Working Group: Network- and machine-learning-based prediction of extreme events

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Title: Chaos, Solitons & Fractals

Source Genre: Journal

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Pages: - Volume / Issue: 114 Sequence Number: - Start / End Page: 364 - 369 Identifier: -