Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Multimachine Stability01:25

Multimachine Stability

229
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
229
Neural Circuits01:25

Neural Circuits

1.6K
Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
1.6K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Relaxed conditions and PSO-based optimization for the problem of Mittag-Leffler synchronization and its application in image restoration for fractional-order octonion-valued two-layer neural networks.

Neural networks : the official journal of the International Neural Network Society·2026
Same author

Association between chrononutrition patterns and metabolic dysfunction-associated steatotic liver disease in adolescents: a population-based study.

Eating and weight disorders : EWD·2026
Same author

Hospitalization costs and out-of-pocket expenses for stroke patients in mainland China.

BMC health services research·2026
Same author

Multi-μ-stability and fixed-time multistability of switched fuzzy neural networks with discontinuous activation functions.

Neural networks : the official journal of the International Neural Network Society·2026
Same author

Multiscale Attention Unet: An Innovative Approach for Segmentation of Optic Disc and Optic Cup in Early Detection of Retinopathy.

Ophthalmology science·2026
Same author

SACI framework-based fixed-time learning control for nonlinear systems with asymmetric constraints.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

Intervention Feasible Region and Driver Risk Capacity Aware Human-Machine Collaborative Safe Trajectory Planning.

IEEE transactions on neural networks and learning systems·2026
Same journal

A Unified Differential Denoising Learning Framework With a Pre-Trained Model and Fuzzy Graph Networks for Drug-Drug Interaction Prediction.

IEEE transactions on neural networks and learning systems·2026
Same journal

Self-Supervised Continuous Dynamic Graph Representation Learning via Hawkes Processes.

IEEE transactions on neural networks and learning systems·2026
Same journal

cPU: Consistent Risk Estimator for Positive-Unlabeled Learning.

IEEE transactions on neural networks and learning systems·2026
Same journal

Tuning-Free Latent Diffusion Models for Ultrahigh-Resolution Image Editing.

IEEE transactions on neural networks and learning systems·2026
Same journal

Hidden Data Recovery and Forecasting via Next-Generation Reservoir Computing With Multiscale Delay Selection.

IEEE transactions on neural networks and learning systems·2026
See all related articles

Related Experiment Video

Updated: Sep 11, 2025

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
08:07

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Published on: March 9, 2019

7.9K

Observer-Based Event-Triggered Fault-Tolerant Synchronization for Memristive Neural Networks Subject to Multiple

Mingxin Wang, Song Zhu, Xiaoyang Liu

    IEEE Transactions on Neural Networks and Learning Systems
    |August 13, 2025
    PubMed
    Summary
    This summary is machine-generated.

    This study addresses memristive neural network (MNN) synchronization under multiple failures using novel fault observers and event-triggered control. Achieved finite-time and fixed-time synchronization, enhancing MNN resilience.

    More Related Videos

    Simultaneous Video-EEG-ECG Monitoring to Identify Neurocardiac Dysfunction in Mouse Models of Epilepsy
    11:54

    Simultaneous Video-EEG-ECG Monitoring to Identify Neurocardiac Dysfunction in Mouse Models of Epilepsy

    Published on: January 29, 2018

    25.8K
    Fabrication of Magnetic Platforms for Micron-Scale Organization of Interconnected Neurons
    09:54

    Fabrication of Magnetic Platforms for Micron-Scale Organization of Interconnected Neurons

    Published on: July 14, 2021

    4.9K

    Related Experiment Videos

    Last Updated: Sep 11, 2025

    Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
    08:07

    Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

    Published on: March 9, 2019

    7.9K
    Simultaneous Video-EEG-ECG Monitoring to Identify Neurocardiac Dysfunction in Mouse Models of Epilepsy
    11:54

    Simultaneous Video-EEG-ECG Monitoring to Identify Neurocardiac Dysfunction in Mouse Models of Epilepsy

    Published on: January 29, 2018

    25.8K
    Fabrication of Magnetic Platforms for Micron-Scale Organization of Interconnected Neurons
    09:54

    Fabrication of Magnetic Platforms for Micron-Scale Organization of Interconnected Neurons

    Published on: July 14, 2021

    4.9K

    Area of Science:

    • Control Systems Engineering
    • Computational Neuroscience
    • Artificial Intelligence

    Background:

    • Memristive Neural Networks (MNNs) are crucial for advanced computing but susceptible to multiple failures.
    • Ensuring reliable operation of MNNs under fault conditions is a significant challenge.

    Purpose of the Study:

    • To investigate the synchronization problem of MNNs under multiple, coupled faults.
    • To develop fault-tolerant synchronization strategies for robust MNN performance.

    Main Methods:

    • Introduced a generalized fault model for MNNs, encompassing various fault types.
    • Designed fault function observers using intermediate variables and state/output feedback.
    • Developed event-triggered, fault-tolerant synchronization schemes based on Halanay-type inequalities.

    Main Results:

    • Successfully constructed fault function observers to detect and estimate multiple failures.
    • Achieved finite-time and fixed-time synchronization/quasi-synchronization through designed control schemes.
    • Demonstrated the effectiveness of the proposed methods via simulation and comparative experiments.

    Conclusions:

    • The developed fault observers and event-triggered synchronization strategies effectively ensure the reliable synchronization of MNNs despite multiple failures.
    • The proposed methods offer robust fault-tolerant control solutions for memristive neural networks.