Title :
Fuzzy hyperline segment clustering neural network
Author :
Kulkarni, U.V. ; Sontakke, T.R. ; Kulkarni, A.B.
Author_Institution :
Dept. of Electron. & Comput. Sci., SGGS Coll. of Eng., Nanded, India
fDate :
3/1/2001 12:00:00 AM
Abstract :
A fuzzy hyperline segment clustering neural network (FHLSCNN) and its learning algorithm is proposed. This algorithm can learn ill-defined nonlinear cluster boundaries in a few passes and is suitable for on-line cluster boundaries in a few passes and is suitable for on-line adaption. The FHLSCNN is superior compared to the fuzzy min-max clustering neural network (FMN) proposed by Simpson
Keywords :
fuzzy neural nets; learning (artificial intelligence); pattern clustering; fuzzy hyperline segment clustering neural network; learning algorithm;
Journal_Title :
Electronics Letters
DOI :
10.1049/el:20010198
