Modeling hyperchaotic datasets for neural networks

Modeling hyperchaotic datasets for neural networks

This work is aimed at the studies related to neurocryptography. The paper represents the studies of hyperchaotic mappings and their construction based on the attractors and the research of image noise characteristics using the attractors and their performance. The conducted experiments have demonstr...

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Bibliografiset tiedot
Päätekijät:	Shiriaev, E. M., Ширяев, Е. М., Bezuglova, E. S., Безуглова, Е. С., Kucherov, N. N., Кучеров, Н. Н., Valuev, G. V., Валуев, Г. В.
Aineistotyyppi:	Статья
Kieli:	English
Julkaistu:	Springer Science and Business Media Deutschland GmbH 2022
Aiheet:	Chaos theory Saito generator Ressler attractor Neurocryptography Hyperchaos Liapunov generator Lorentz attractor
Linkit:	https://dspace.ncfu.ru/handle/20.500.12258/19639
Tagit:	Lisää tagi Ei tageja, Lisää ensimmäinen tagi!

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