Title :
A comparison between habituation and conscience mechanism in self-organizing maps
Author :
Rizzo, R. ; Chella, A.
Author_Institution :
Inst. di Calcolo e Reti ad Alte Prestazioni, ICAR-CNR, Palermo
fDate :
5/1/2006 12:00:00 AM
Abstract :
In this letter, a preliminary study of habituation in self-organizing networks is reported. The habituation model implemented allows us to obtain a faster learning process and better clustering performances. The habituable neuron is a generalization of the typical neuron and can be used in many self-organizing network models. The habituation mechanism is implemented in a SOM and the clustering performances of the network are compared to the conscience learning mechanism that follows roughly the same principle but is less sophisticated
Keywords :
learning (artificial intelligence); self-organising feature maps; conscience learning mechanism; habituable neuron; habituation model; self-organizing maps; Algorithm design and analysis; Instruction sets; Intelligent networks; Learning systems; Neurons; Nonhomogeneous media; Self organizing feature maps; Self-organizing networks; Unsupervised learning; Vector quantization; Conscience learning; habituation; self-organizing feature maps; unsupervised learning; Algorithms; Artificial Intelligence; Conscience; Habituation, Psychophysiologic; Information Storage and Retrieval; Neural Networks (Computer); Pattern Recognition, Automated; Systems Theory;
Journal_Title :
Neural Networks, IEEE Transactions on
DOI :
10.1109/TNN.2006.872354