American Psychological Association 6th edition

Lange, M. M., & Lange, A. M. (2022). Information-Theoretic Lower Bounds to Error Probability for the Models of Noisy Discrete Source Coding and Object Classification. Pattern Recognition and Image Analysis, 32(3), 570-574. https://doi.org/10.1134/s105466182203021 x

ISO-690 (author-date, English)

LANGE, M. M. und LANGE, A. M., 2022. Information-Theoretic Lower Bounds to Error Probability for the Models of Noisy Discrete Source Coding and Object Classification. Pattern Recognition and Image Analysis. 1 September 2022. Vol. 32, no. 3, p. 570-574. DOI 10.1134/s105466182203021 x.

Modern Language Association 9th edition

Lange, M. M., und A. M. Lange. „Information-Theoretic Lower Bounds to Error Probability for the Models of Noisy Discrete Source Coding and Object Classification“. Pattern Recognition and Image Analysis, Bd. 32, Nr. 3, September 2022, S. 570-4, https://doi.org/10.1134/s105466182203021 x.

Mohr Siebeck - Recht (Deutsch - Österreich)

Lange, M. M./Lange, A. M.: Information-Theoretic Lower Bounds to Error Probability for the Models of Noisy Discrete Source Coding and Object Classification, Pattern Recognition and Image Analysis 2022, 570-574.

Emerald - Harvard

Lange, M.M. und Lange, A.M. (2022), „Information-Theoretic Lower Bounds to Error Probability for the Models of Noisy Discrete Source Coding and Object Classification“, Pattern Recognition and Image Analysis, Vol. 32 No. 3, S. 570-574.

Achtung: Diese Zitate sind unter Umständen nicht zu 100% korrekt.