A new learning algorithm for pattern classification using cellular neural networks
Giuseppe Grassi, Eugenio Di Sciascio · 2002
In this paper a new learning algorithm for pattern classification using cellular neural networks is described. In particular, it is shown that patterns belonging to the training set as well as patterns outside it can be reliably classified using the proposed algorithm. Finally, comparisons with well-established classification techniques are carried out, with the aim to highlight the performances of the approach developed herein.