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Energy-efficient distributed spiking neural network for wireless edge intelligence
The spiking neural network (SNN) is distinguished by its ultra-low power consumption,
making it attractive for resource-limited edge intelligence. This paper investigates an energy …
making it attractive for resource-limited edge intelligence. This paper investigates an energy …
Enhancing cybersecurity in the internet of things environment using bald eagle search optimization with hybrid deep learning
Nowadays, the Internet of Things (IoT) has become a rapid development; it can be employed
by cyber threats in IoT devices. A correct system to recognize malicious attacks at IoT …
by cyber threats in IoT devices. A correct system to recognize malicious attacks at IoT …
Artificial intelligence techniques for next-generation massive satellite networks
Space communications, particularly massive satellite networks, re-emerged as an appealing
candidate for next generation networks due to major advances in space launching …
candidate for next generation networks due to major advances in space launching …
Artificial intelligence techniques for next-generation mega satellite networks
Space communications, particularly massive satellite networks, re-emerged as an appealing
candidate for next generation networks due to major advances in space launching …
candidate for next generation networks due to major advances in space launching …
Spiking Neural Networks for Detecting Satellite Internet of Things Signals
With the rapid growth of Internet of Things (IoT) networks, ubiquitous coverage is becoming
increasingly necessary. Low earth orbit (LEO) satellite constellations for the IoT have been …
increasingly necessary. Low earth orbit (LEO) satellite constellations for the IoT have been …
Deep learning in wireless communications for physical layer
J Zhao, C Liu, J Liao, D Wang - Physical Communication, 2024 - Elsevier
Current wireless communication faces challenges of spectrum congestion, interference, and
accommodating Internet of Things and 5G demands. Artificial intelligence (AI) has recently …
accommodating Internet of Things and 5G demands. Artificial intelligence (AI) has recently …
[HTML][HTML] Enhancing IoT Security Using GA-HDLAD: A Hybrid Deep Learning Approach for Anomaly Detection
I Mutambik - Applied Sciences, 2024 - mdpi.com
The adoption and use of the Internet of Things (IoT) have increased rapidly over recent
years, and cyber threats in IoT devices have also become more common. Thus, the …
years, and cyber threats in IoT devices have also become more common. Thus, the …
Intelligent index classification method based on machine learning for detection of reference signal in 5G networks
In order to maintain stable communication in 5G wireless networks, the link between a 5G
base station and user equipment (UE) should be constantly monitored and adapted to the …
base station and user equipment (UE) should be constantly monitored and adapted to the …
Analysis and Prediction of Mobile Industrial Internet of Things (IIoT) Communications Based on FL-GLP-Net
The number of mobile users and applications is rising quickly due to the deployment of fifth-
generation (5G) communication technology. The prevalence of smart devices and Internet of …
generation (5G) communication technology. The prevalence of smart devices and Internet of …
Spiking-unet: Spiking neural networks for spectrum occupancy monitoring
K Dakic, B Al Homssi… - 2024 IEEE Wireless …, 2024 - ieeexplore.ieee.org
With the exponential growth of the Internet of Things (IoT) landscape and the resulting
spectrum congestion, innovative techniques for spectrum monitoring are crucial. This paper …
spectrum congestion, innovative techniques for spectrum monitoring are crucial. This paper …