Mackey Glass Time Series Prediction using Radial Basis Function (RBF) Neural Network

Mackey Glass Time Series Prediction using Radial Basis Function (RBF) Neural Network
1.1K Downloads
Updated 27 Feb 2018

View License

In this submission I implemented an radial basis function (RBF) neural network for the prediction of chaotic time-series prediction. In particular a Mackey Glass time series prediction model is designed, the model can predict few steps forward values using the past time samples. The RBF is trained using conventional gradient descent learning algorithm and the kernel function is the Gaussian kernel with centers and spreads obtained from K-mean clustering algorithm.

Cite As

Shujaat Khan (2024). Mackey Glass Time Series Prediction using Radial Basis Function (RBF) Neural Network (https://www.mathworks.com/matlabcentral/fileexchange/66216-mackey-glass-time-series-prediction-using-radial-basis-function-rbf-neural-network), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2017a
Compatible with any release
Platform Compatibility
Windows macOS Linux
Categories
Find more on Statistics and Machine Learning Toolbox in Help Center and MATLAB Answers

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Time_Series_Prediction/html/

Version Published Release Notes
1.0.0.0