Title :
CBP networks as a generalized neural model
Author :
Ridella, Sandro ; Rovetta, Stefano ; Zunino, Rodolfo
Author_Institution :
Dept. of Biophys. & Electron. Eng., Univ. of Genova, Italy
Abstract :
This paper analyzes the circular backpropagation network, a simple modification of the multilayer perceptron with interesting practical properties, especially well-suited to cope with pattern classification tasks. The proposed model unifies the two main representation paradigms found in the class of mapping networks for classification, namely, the surface-based and the prototype-based schemes, while retaining the advantage of being trainable by back-propagation. Multilayer perceptrons, radial-basis-function networks and vector-quantization networks are shown to be implementable with small modifications to the model under study
Keywords :
backpropagation; multilayer perceptrons; pattern classification; CBP networks; circular backpropagation network; generalized neural model; multilayer perceptron; pattern classification; prototype-based scheme; radial-basis-function networks; surface-based scheme; vector-quantization networks; Backpropagation; Electronic mail; Multi-layer neural network; Multilayer perceptrons; Neural networks; Nonhomogeneous media; Pattern analysis; Pattern classification; Polynomials; Prototypes;
Conference_Titel :
Neural Networks,1997., International Conference on
Conference_Location :
Houston, TX
Print_ISBN :
0-7803-4122-8
DOI :
10.1109/ICNN.1997.611666