To undrestand the main idea of convolutional neural networks, specially for the new comers to CNNs we made these codes small as it is possible and we added many comments in the codes almost each line has a comment.
the CNN in these codes is trained using ELM, and the local fields are independent from each other (no overlap).
and please if you used this toolbox ,cite my name in your paper.
for any referances , you can start with these ones that i used in my work:
 C. M. Vong, “Local Receptive Fields Based Extreme Learning Machine,” IEEE Comput. Intell. Mag., vol. 10, no. 2, pp. 18–29, 2015.
 G. Huang, N. Liang, H. Rong, P. Saratchandran, and N. Sundararajan, “On-Line Sequential Extreme Learning Machine Review of Extreme Learning Ma- chine ( ELM ) Proposed Online Sequential Ex-,” Int. Conf. Comput. Intell., no. Ci, 2005.
 O. Barak, M. Rigotti, and S. Fusi, “The Sparseness of Mixed Selectivity Neurons Controls the Generalization–Discrimination Trade-Off,” J. Neurosci., vol. 33, no. 9, pp. 3844–3856, 2013.
BERGHOUT Tarek (2023). Convolutional neural networks CNNs based ELM (https://www.mathworks.com/matlabcentral/fileexchange/71325-convolutional-neural-networks-cnns-based-elm), MATLAB Central File Exchange. Retrieved .
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