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 Experiment Videos

Online modeling with tunable RBF network.

Hao Chen1, Yu Gong, Xia Hong

  • 1School of Systems Engineering, University of Reading, Reading, West Berkshire RG6 6UR, UK. hao.chen@pgr.reading.ac.uk

IEEE Transactions on Cybernetics
|October 26, 2012
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

Modeling with Differential Equations01:25

Modeling with Differential Equations

Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...
Neural Regulation01:37

Neural Regulation

Digestion begins with a cephalic phase that prepares the digestive system to receive food. When our brain processes visual or olfactory information about food, it triggers impulses in the cranial nerves innervating the salivary glands and stomach to prepare for food.

You might also read

Related Articles

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

Sort by
Same author

M phase phosphorylation of the epigenetic regulator UHRF1 regulates its physical association with the deubiquitylase USP7 and stability.

Proceedings of the National Academy of Sciences of the United States of America·2012
Same author

Biosynthesis of ethyl oleate, a primer pheromone, in the honey bee (Apis mellifera L.).

Insect biochemistry and molecular biology·2012
Same author

Co-delivery strategies based on multifunctional nanocarriers for cancer therapy.

Current drug metabolism·2012
Same author

Efficacy of gemifloxacin for the treatment of experimental Staphylococcus aureus keratitis.

Journal of ocular pharmacology and therapeutics : the official journal of the Association for Ocular Pharmacology and Therapeutics·2012
Same author

Expression profile analysis of the polygalacturonase-inhibiting protein genes in rice and their responses to phytohormones and fungal infection.

Plant cell reports·2012
Same author

Characterizing natural dissolved organic matter in a freshly submerged catchment (Three Gorges Dam, China) using UV absorption, fluorescence spectroscopy and PARAFAC.

Water science and technology : a journal of the International Association on Water Pollution Research·2012
Same journal

An Evolutionary Algorithm Assisted by an Ensemble of Pareto-Optimal Surrogate Models.

IEEE transactions on cybernetics·2026
Same journal

A Quantum Self-Attention Neural Network Model on Quantum Circuits.

IEEE transactions on cybernetics·2026
Same journal

Semi-Explicit Solution of Some Discrete-Time Higher-Order-Cost Mean-Field-Type Control.

IEEE transactions on cybernetics·2026
Same journal

A Novel One-Step Small Object Detector for Autonomous Aerial Vehicles.

IEEE transactions on cybernetics·2026
Same journal

Online Data-Driven-Based Optimal Output Tracking Control Without Initial Stabilizing Policy.

IEEE transactions on cybernetics·2026
Same journal

Digital Redesign-Based Interval State Estimation for Continuous Systems With Aperiodic Discrete Measurements.

IEEE transactions on cybernetics·2026
See all related articles

This study introduces an innovative online modeling algorithm for nonlinear and nonstationary systems. It efficiently adapts radial basis function (RBF) networks using multi-innovation recursive least squares and quantum particle swarm optimization for improved performance.

Area of Science:

  • * Computational intelligence and machine learning.
  • * Adaptive systems modeling.
  • * Nonlinear system identification.

Background:

  • * Modeling nonlinear and nonstationary systems presents significant challenges.
  • * Existing methods often struggle with dynamic system changes and model sparsity.
  • * Radial basis function (RBF) networks offer a flexible framework for nonlinear approximation.

Purpose of the Study:

  • * To develop a novel online modeling algorithm for nonlinear and nonstationary systems.
  • * To enhance the adaptability and efficiency of RBF neural networks in dynamic environments.
  • * To achieve accurate modeling with a sparse representation of complex systems.

Main Methods:

  • * Employing a radial basis function (RBF) neural network with tunable centers and covariance matrices.

Related Experiment Videos

  • * Utilizing a multi-innovation recursive least squares (MRLS) algorithm for online weight adaptation.
  • * Integrating quantum particle swarm optimization (QPSO) for optimizing new node parameters and structure.

    • Main Results:

    • * The proposed algorithm effectively tracks local characteristics in nonstationary systems.
    • * It achieves accurate modeling with a very sparse RBF network structure.
    • * Simulation results demonstrate superior performance compared to existing online modeling approaches.

    Conclusions:

    • * The combination of MRLS weight adaptation and QPSO structure optimization offers a powerful approach for online system modeling.
    • * The algorithm provides a robust and efficient solution for modeling complex nonlinear and nonstationary dynamics.
    • * This novel method significantly advances the state-of-the-art in adaptive system identification.