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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Actualizado 27 feb 2018

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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.

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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. Recuperado .

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Versión Publicado Notas de la versión
1.0.0.0