American Psychological Association 6th edition

Kamalakannan, S., Saravanan, V., Shankar, B., & Kumar, N. (2026). Securing 5 G Networks: An Anomaly Detection System Empowered by Bidirectional 3 D Quasi-Recurrent Neural Network. Journal of Circuits, Systems & Computers, 35(1), 1-24. https://doi.org/10.1142/S0218126625503621

ISO-690 (author-date, English)

KAMALAKANNAN, S., SARAVANAN, V., SHANKAR, B. Maruthi und KUMAR, N. Sathish, 2026. Securing 5 G Networks: An Anomaly Detection System Empowered by Bidirectional 3 D Quasi-Recurrent Neural Network. Journal of Circuits, Systems & Computers. 15 Januar 2026. Vol. 35, no. 1, p. 1-24. DOI 10.1142/S0218126625503621.

Modern Language Association 9th edition

Kamalakannan, S., V. Saravanan, B. Shankar, und N. Kumar. „Securing 5 G Networks: An Anomaly Detection System Empowered by Bidirectional 3 D Quasi-Recurrent Neural Network.“. Journal of Circuits, Systems & Computers, Bd. 35, Nr. 1, Januar 2026, S. 1-24, https://doi.org/10.1142/S0218126625503621.

Mohr Siebeck - Recht (Deutsch - Österreich)

Kamalakannan, S./Saravanan, V./Shankar, B. Maruthi/Kumar, N. Sathish: Securing 5 G Networks: An Anomaly Detection System Empowered by Bidirectional 3 D Quasi-Recurrent Neural Network., Journal of Circuits, Systems & Computers 2026, 1-24.

Emerald - Harvard

Kamalakannan, S., Saravanan, V., Shankar, B. und Kumar, N. (2026), „Securing 5 G Networks: An Anomaly Detection System Empowered by Bidirectional 3 D Quasi-Recurrent Neural Network.“, Journal of Circuits, Systems & Computers, Vol. 35 No. 1, S. 1-24.

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