Function Approximation Using Neural Network Without using Toolbox

Versione 1.0.0.0 (118 KB) da Alireza

This code implements the basic backpropagation of error learning algorithm

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Aggiornato 4 mag 2016

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This code implements the basic back propagation of error learning algorithm. the network has tanh hidden neurons and a linear output neuron, and applied for predicting y=sin(2pix1)*sin(2pix2).
We didn't use any feature of neural network toolbox.

Cita come

Alireza (2026). Function Approximation Using Neural Network Without using Toolbox (https://it.mathworks.com/matlabcentral/fileexchange/17355-function-approximation-using-neural-network-without-using-toolbox), MATLAB Central File Exchange. Recuperato marzo 10, 2026.

Compatibilità della release di MATLAB

Creato con R2007a

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Categorie

AI and Statistics > Deep Learning Toolbox > Train Deep Neural Networks > Function Approximation, Clustering, and Control > Function Approximation and Clustering > Define Shallow Neural Network Architectures >

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Riconoscimenti

Ispirato: Orthogonal Least Squares Algorithm for RBF Networks, Back Propogation Algorithm

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Versione	Pubblicato	Note della release
1.0.0.0	4 mag 2016	BSD License	Scarica