A Systematic review on the energy efficiency of dynamic clustering in a heterogeneous environment of Wireless Sensor Networks (WSNs)
There are a variety of applications for wireless sensor networks (WSNs), such as military,
health monitoring systems, natural disasters, smartphones, and other surveillance systems …
health monitoring systems, natural disasters, smartphones, and other surveillance systems …
Variance-Constrained Resilient State Estimation for Time-Varying Neural Networks with Random Saturation Observation Under Uncertain Occurrence Probability
Y Gao, J Hu, H Yu, J Du, C Jia - Neural Processing Letters, 2023 - Springer
This paper studies the variance-constrained resilient H∞ state estimation problem for
discrete time-varying uncertain recurrent neural networks with random saturation …
discrete time-varying uncertain recurrent neural networks with random saturation …
Exploring the effects of Caputo fractional derivative in spiking neural network training
NM Gyöngyössy, G Eros, J Botzheim - Electronics, 2022 - mdpi.com
Fractional calculus is an emerging topic in artificial neural network training, especially when
using gradient-based methods. This paper brings the idea of fractional derivatives to spiking …
using gradient-based methods. This paper brings the idea of fractional derivatives to spiking …
A supervised learning algorithm to binary classification problem for spiking neural networks
S Wang, C Li - 2021 8th International Conference on …, 2021 - ieeexplore.ieee.org
Spiking neural networks (SNN) are known as the third generation neural network, which can
simulate biological neural networks signals and has stronger computing power. In contrast …
simulate biological neural networks signals and has stronger computing power. In contrast …