Name
Abstract | ||
|---|---|---|
In this paper fuzzy hypersphere neural network (FHSNN) is proposed with its learning algorithm. The FHSNN utilizes fuzzy sets as pattern classes in which each fuzzy set is an union of fuzzy set hyperspheres. Its performance is compared with other two fuzzy neural networks and found to be superior with respect to the training time, recall time per pattern and the generalization |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1109/FUZZ.2001.1008961 | Fuzzy Systems, 2001. The 10th IEEE International Conference |
Keywords | Field | DocType |
fuzzy neural nets,fuzzy set theory,learning (artificial intelligence),pattern classification,FHSNN,fuzzy hypersphere neural network classifier,fuzzy sets,generalization,learning algorithm,pattern classes,pattern classification,pattern clustering,recall time,training time | Neuro-fuzzy,Fuzzy classification,Pattern recognition,Computer science,Fuzzy set operations,Fuzzy logic,Hypersphere,Fuzzy set,Artificial intelligence,Adaptive neuro fuzzy inference system,Fuzzy associative matrix,Machine learning | Conference |
Volume | Citations | PageRank |
3 | 3 | 0.43 |
References | Authors | |
9 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kulkarni, U.V. | 1 | 8 | 1.32 |
| Sontakke, T.R. | 2 | 5 | 0.81 |