TY - GEN
T1 - New radial basis function neural network architecture for pattern classification
T2 - 19th Iberoamerican Congress on Pattern Recognition, CIARP 2014
AU - Sossa, Humberto
AU - Cortés, Griselda
AU - Guevara, Elizabeth
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2014.
PY - 2014
Y1 - 2014
N2 - This paper presents the initial results concerning a new Radial Basis Function Artificial Neural Network (RBFNN) architecture for pattern classification. Performance of the new architecture is demonstrated with different data sets. Its efficiency is also compared with different classification methods reported in literature: Multilayer Perceptron, Standard Radial Basis Neural Networks, KNN and Minimum Distance classifiers, showing a much better performance. Results are only given for problems using two features.
AB - This paper presents the initial results concerning a new Radial Basis Function Artificial Neural Network (RBFNN) architecture for pattern classification. Performance of the new architecture is demonstrated with different data sets. Its efficiency is also compared with different classification methods reported in literature: Multilayer Perceptron, Standard Radial Basis Neural Networks, KNN and Minimum Distance classifiers, showing a much better performance. Results are only given for problems using two features.
UR - http://www.scopus.com/inward/record.url?scp=84949154441&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-12568-8_86
DO - 10.1007/978-3-319-12568-8_86
M3 - Contribución a la conferencia
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 706
EP - 713
BT - Progress in Pattern Recognition Image Analysis, Computer Vision and Applications - 19th Iberoamerican Congress, CIARP 2014, Proceedings
A2 - Bayro-Corrochano, Eduardo
A2 - Hancock, Edwin
PB - Springer Verlag
Y2 - 2 November 2014 through 5 November 2014
ER -