We present the use of the MATLAB Neural Network Toolbox (NN Toolbox) in simulations of neural networks. We suggest ways for undergraduate students to solve a character recognition problem with feed‐forward neural networks. The software provides the user with a very simple way to define several neural network architectures with different parameters. The solution of the character recognition problem is described from the beginning: collecting the data, data encoding, defining the input‐output mapping architecture to the training, and testing the neural networks with the NN Toolbox. © 2005 Wiley Periodicals, Inc. Comput Appl Eng Educ 13: 66–71, 2005; Published online in Wiley InterScience (www.interscience.wiley.com); DOI 10.1002/cae.20031. Number of times cited: 6 2016 IEEE International Conference on Signal and Image Processing (ICSIP) Beijing, China 2016 IEEE International Conference on Signal and Image Processing (ICSIP) IEEE, (2016).

1. Matlab 2016a Key
2. Matlab 2016a User Guide Neural Network Toolbox

978-1-5090-2377-6 Dengfeng Li, PengFei Yu, Haiyan Li and Ge Peng Printed New Tai Lue character recognition based on BP neural network, (2016). 339 3, 10.1109/SIPROCESS.20. Hai Ping Li, J.C.M. Kao and W.-P. Sung, The Application of MATLAB in Automatic Fingerprint Recognition System of Police, MATEC Web of Conferences, 63, (04020), (2016). 2006 Seventh Mexican International Conference on Computer Science San Luis Potosi, Mexico 2006 Seventh Mexican International Conference on Computer Science IEEE, (2006).

Matlab 2016a Key

Matlab 2016a User Guide Neural Network Toolbox

0-7695-2666-7 Arturo Mendez, Emilio Rosello, Maria Lado, Jacinto Dacosta, David Torres and Manuel Cota IMO.Net Artificial Neural Networks: an object-oriented reusable software component library to integrate Matlab Neural Networks functionality, (2006). 159 1, 10.1109/ENC.2006.18 http://ieeexplore.ieee.org/document/4020875/.