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

Mackey Glass Time Series Prediction using Radial Basis Function (RBF) Neural Network
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Updated Tue, 27 Feb 2018 03:10:10 +0000

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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
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Version Published Release Notes
1.0.0.0