A hybrid Modified Black Widow Optimization and PSO Algorithm: Application in Feature Selection for Cognitive Radio Networks

Chaabane, Sarra Ben; Boualleguet, Kais; Belazi, Akram; Kharbech, Sofiane; Bouallègue, Ammar

doi:10.1109/apcc55198.2022.9943598

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Cited by 3 publications

References 19 publications

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A survey and recent advances in black widow optimization: variants and applications

Shehab,

Shambour,

Abu Hashem

et al. 2024

Neural Comput & Applic

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A survey and recent advances in black widow optimization: variants and applications

Shehab,

Shambour,

Abu Hashem

et al. 2024

Neural Comput & Applic

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Design and Implementation for EEG Artifact Detection and Removal Technique for Neuro Training Application

Kanna,

Jyothi,

Ambikapathy

et al. 2024

Advances in Medical Technologies and Clinical Practice

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A complete and rigorous literature evaluation focused on the detection and elimination of artifacts from EEG signals was presented in the preceding chapter. Issue-wise solution approaches and their limitations were also discussed which ultimately resulted in identifying the gaps in the proposed work and scope of the research work. In this chapter, the detailed explanation of system design and its implementation is discussed. The main focus of the anticipated research is to identify and remove the unwanted signals known as artifacts from the recorded EEG signals.

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Smart Detection and Removal of Artifacts in Cognitive Signals Using Biomedical Signal Intelligence Applications

Kishore Kanna,

Yamuna Devi,

Gomalavalli

et al. 2023

Quantum Innovations at the Nexus of Biomedical Intelligence

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A complete and detailed literature evaluation concentrating on the detection and elimination of artifacts from EEG data was described in the preceding chapter. Issue-wise solution suggestions and their limitations were also studied, which eventually led to finding the gaps in the recommended task and scope of the study activity. In this chapter, the complete explanation of system design and its implementation is addressed. The principal objective of the proposed research is to identify and eliminate the undesired signals known as artifacts from the collected EEG data. This chapter spoke about the design of the system and its implementation. In this chapter specifics of EEG acquisition methods have been discussed. The initial stage in EEG signal processing is recording EEG data from the individuals. It also looks into the categorization of EEG data by sort. The obtained EEG data was sorted into two categories: normal and epileptic.

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A hybrid Modified Black Widow Optimization and PSO Algorithm: Application in Feature Selection for Cognitive Radio Networks

Cited by 3 publications

References 19 publications

A survey and recent advances in black widow optimization: variants and applications

A survey and recent advances in black widow optimization: variants and applications

Design and Implementation for EEG Artifact Detection and Removal Technique for Neuro Training Application

Smart Detection and Removal of Artifacts in Cognitive Signals Using Biomedical Signal Intelligence Applications

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