Dynamic associative neural memories
Associative neural memories
A normal form projection algorithm for associative memory
Associative neural memories
Solving multiclass learning problems via error-correcting output codes
Journal of Artificial Intelligence Research
Neural networks for classification: a survey
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A New Fault Detection and Diagnosis Method for Oil Pipeline Based on Rough Set and Neural Network
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
Supervised projection approach for boosting classifiers
Pattern Recognition
Construction of a neuron-fuzzy classification model based on feature-extraction approach
Expert Systems with Applications: An International Journal
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This paper describes the development of the utility of a dynamic neural network known as projection network for pattern classification. It first gives the derivation of the projection network, and then describes the network architecture and analyzes properties such as equilibrium points and their stability condition. The procedures for utilizing the projection network for pattern classification are established and the benefits are discussed. The proposed classification system is then tested with well-known benchmark data sets, namely the Fisher's iris data, the heart disease data and the credit screening data and the results are compared to other classifiers including Neural Network Rule Base (NNRB), Genetic Algorithm Rule Base (GARB), Rough Set, and C4.5 decision tree. The projection network was proven to be a viable alternative to existing methods.