TY - GEN
T1 - A simple "possibilistic" clustering neural network
AU - Yadid-Pecht, O.
AU - Gur, M.
N1 - Publisher Copyright:
© 1994 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.
PY - 1994/1/1
Y1 - 1994/1/1
N2 - A simple "possibilistic" clustering method, Le. clustering where each datum has a degree of possibility of belonging to the cluster, using a neural net, is suggested. The implementation consists of simple "neurons", requiring only a small number of local connections, collectively performing a diffusion-like process. In spite of its simplicity, this implementation has several advantages over commonly used fuzzy clustering methods. Specifically, it provides the "typicality" notion that is lacking in the well known Fuzzy C Means (FCM) and its derivatives, and is less sensitive to noise.
AB - A simple "possibilistic" clustering method, Le. clustering where each datum has a degree of possibility of belonging to the cluster, using a neural net, is suggested. The implementation consists of simple "neurons", requiring only a small number of local connections, collectively performing a diffusion-like process. In spite of its simplicity, this implementation has several advantages over commonly used fuzzy clustering methods. Specifically, it provides the "typicality" notion that is lacking in the well known Fuzzy C Means (FCM) and its derivatives, and is less sensitive to noise.
UR - http://www.scopus.com/inward/record.url?scp=85115212928&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85115212928
T3 - Proceedings - International Conference on Pattern Recognition
SP - 520
EP - 521
BT - Proceedings of the 12th IAPR International Conference on Pattern Recognition - Conference B
PB - Institute of Electrical and Electronics Engineers
T2 - 12th IAPR International Conference on Pattern Recognition - Conference B: Pattern Recognition and Neural Networks, ICPR 1994
Y2 - 9 October 1994 through 13 October 1994
ER -