Comparative Study of SVM and KNN Machine Learning Algorithm for Spectrum Sensing in Cognitive Radio-Reference-Cited by-同舟云学术

Comparative Study of SVM and KNN Machine Learning Algorithm for Spectrum Sensing in Cognitive Radio

Published:2022-07-20 Issue: Volume: Page:517-527
ISSN:2367-4512
Container-title:Intelligent Communication Technologies and Virtual Mobile Networks
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Author:

Tamilselvi T.,Rajendran V.

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-1844-5_41

Reference23 articles.

1. Akyildiz F, Lee WY, Vuran MC, Mohanty S (2008) A survey on spectrum management in cognitive radio networks. IEEE Commun Mag 46(40):40–48

2. Shilton A, Palaniswami M, Ralph D, Tsoi AC (2005) Incremental training in support vector machines. IEEE Trans Neural Netw 16:114–131

3. Sandya HB et al (2018) A thorough analysis of cognitive radio spectrum sensing methods in communication networks. In: 7th IEEE international conference on communication and signal processing—ICCSP 18, 3rd to 5th April 2018, Melmaruvathur, Tamil Nadu, India

4. Sandya HB et al (2013) Fuzzy rule based feature extraction and classification of time series signal. Int J “Soft Comput Eng” (IJSCE) 3(2). ISSN: 2231-2307

5. Bharathy GT, Rajendran V, Tamilselvi T, Meena M (2020) A study and simulation of spectrum sensing schemes for cognitive radio networks. In: 2020 7th international conference on smart structures and systems (ICSSS), Chennai, India, 2020, pp 1–11. https://doi.org/10.1109/ICSSS49621.2020.9202296

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