Title :
Automatic fusion and splitting of artificial neural elements in optimizing the network size
Author :
Kameyama, Keisuke ; Kosugi, Yukio
Author_Institution :
Tokyo Inst. of Technol., Yokohama, Japan
Abstract :
A three-layered neural network that optimally self-adjusts the number of hidden layer units is proposed. The network combines two techniques: (1) unit fusion which enables an efficient pruning of the redundant units: and (2) linear transformations applied to the chosen hidden layer unit pair output and a modified backpropagation training rule for gradual fusion to reduce pruning shocks. The network was applied to a character recognition problem and it adjusted itself to a minimal configuration at high rate
Keywords :
character recognition; learning systems; neural nets; optimisation; self-adjusting systems; backpropagation training rule; character recognition; fusion; hidden layer self adjusting; neural element splitting; optimisation; pruning; three-layered neural network; Artificial neural networks; Character recognition; Computer networks; Electric shock; Intelligent networks; Mutual information; Neural networks; Pattern classification; Problem-solving; Vectors;
Conference_Titel :
Systems, Man, and Cybernetics, 1991. 'Decision Aiding for Complex Systems, Conference Proceedings., 1991 IEEE International Conference on
Conference_Location :
Charlottesville, VA
Print_ISBN :
0-7803-0233-8
DOI :
10.1109/ICSMC.1991.169926
