Name
Abstract | ||
|---|---|---|
Approximate reasoning approach to pattern recognition consists of linguistic rules tied together by means of two concepts: fuzzy implications and a compositional rule of inference. In this paper, first we study the applicability of different interpretations of fuzzy implication to pattern recognition problem and subsequently compare their performances over a set of synthetic data. Finally, we use the most applicable (according to our study) interpretations of implication for vowel recognition of three different Indian languages and we obtain very promising results. |
Year | DOI | Venue |
|---|---|---|
1996 | 10.1016/0165-0114(95)00095-X | Fuzzy Sets and Systems |
Keywords | Field | DocType |
pattern recognition,approximate reasoning,approximate reasoning approach,vowel recognition,synthetic data | Computer science,Synthetic data,Feature (machine learning),Approximate reasoning,Natural language processing,Artificial intelligence,Pattern recognition problem,Vowel recognition,Fuzzy implication,Pattern recognition,Fuzzy logic,Rule of inference,Machine learning | Journal |
Volume | Issue | ISSN |
77 | 2 | Fuzzy Sets and Systems |
Citations | PageRank | References |
10 | 1.59 | 1 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kumar S. Ray | 1 | 349 | 49.30 |
| J. Ghoshal | 2 | 16 | 2.53 |