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Analyzing EEG patterns in young adults exposed to different acrophobia levels: a VR study
Introduction The primary objective of this research is to examine acrophobia, a widely
prevalent and highly severe phobia characterized by an overwhelming dread of heights …
prevalent and highly severe phobia characterized by an overwhelming dread of heights …
Hybrid models for direct normal irradiance forecasting: A case study of Ghardaia zone (Algeria)
This study presents a resilient model for accurately predicting annual solar radiation in
Ghardaia, Algeria, utilizing a locally-sourced database. The model integrates temperature …
Ghardaia, Algeria, utilizing a locally-sourced database. The model integrates temperature …
Exploring the dynamic behavior of system model construction with unknown parameters and achieving synchronous control of fuzzy neural networks
J Jie, P Zhang, Y Yang, Q Sui - Chaos, Solitons & Fractals, 2024 - Elsevier
This study proposes a method that combines constant terms with state variables to construct
the target system model. The three-dimensional system model is used for verification …
the target system model. The three-dimensional system model is used for verification …
[HTML][HTML] A construction method for achieving tunable multi-wing complex chaotic system transformation from 'dart-shaped'to 'circular'
M Yan, X Liu, C Li, J Zhu - Alexandria Engineering Journal, 2024 - Elsevier
To address the limitations of traditional untunable multi-wing chaotic systems in terms of
stability and security, this study proposes a novel method for constructing a tunable multi …
stability and security, this study proposes a novel method for constructing a tunable multi …
[PDF][PDF] Deep learning for eeg-based motor imagery classification: Towards enhanced human-machine interaction and assistive robotics
This study presents a comprehensive exploration of EEG-based motor imagery classification
using advanced deep learning architectures. Focusing on six distinct motor imagery classes …
using advanced deep learning architectures. Focusing on six distinct motor imagery classes …
[HTML][HTML] Dynamic Analysis and Implementation of FPGA for a New 4D Fractional-Order Memristive Hopfield Neural Network
F Yu, S Zhang, D Su, Y Wu, YM Gracia, H Yin - Fractal and Fractional, 2025 - mdpi.com
Memristor-based fractional-order chaotic systems can record information from the past,
present, and future, and describe the real world more accurately than integer-order systems …
present, and future, and describe the real world more accurately than integer-order systems …
[HTML][HTML] Edge-of-Chaos Kernel and Dynamic Analysis of a Hopfield Neural Network with a Locally Active Memristor
L Zhang, Y Ma, R Jiang, Z Yang, X Pu, Z Li - Electronics, 2025 - mdpi.com
Locally active memristors with an Edge-of-Chaos kernel (EOCK) represent a significant
advancement in the simulation of neuromorphic dynamics. However, current research on …
advancement in the simulation of neuromorphic dynamics. However, current research on …
[HTML][HTML] Multi-Buoy Deployment Method Based on an Improved Tuna Swarm Optimizer Enhanced with Fractional-Order Calculus Method for Marine Observation
Ocean buoys play a critical role in marine hydrological, water quality, and meteorological
monitoring, with applications in navigation, environmental observation, and communication …
monitoring, with applications in navigation, environmental observation, and communication …
[PDF][PDF] Semi-mind controlled robots based on Reinforcement Learning for Indoor Application.
This paper presents a solution to this challenge by introducing interactive feedback derived
from brain signals to train robots using deep reinforcement learning, particularly in the …
from brain signals to train robots using deep reinforcement learning, particularly in the …
Recurrent Neural Network with Backstep** controller based Fractional-Order Chaotic System based Solution for Secure Communication and Image Encryption
Synchronisation of Fractional-order Non-linear systems can be used by incorporating
additional security attributes. In this work, a Recurrent Neural network with Backstep** …
additional security attributes. In this work, a Recurrent Neural network with Backstep** …