Name
Abstract | ||
|---|---|---|
An analog sequential architecture for efficient neuro-fuzzy models implementation is proposed. The best features of digital and analog domains are combined to provide a high degree of flexibility (in terms of number of inputs, number of membership functions per input and number of fuzzy rules) when handling real world tasks. The performance estimations show a good area/throughput ratio, thus making the architecture suitable for a wide range of applications. |
Year | DOI | Venue |
|---|---|---|
1997 | 10.1007/BFb0020314 | ICANN |
Keywords | Field | DocType |
neuro-fuzzy models vlsi implementation,analog sequential architecture,neuro fuzzy,membership function | Neuro-fuzzy,Computer science,Fuzzy logic,Fuzzy control system,Throughput,Artificial neural network,Very-large-scale integration,Computer engineering,Membership function,Embedded system,Fuzzy rule,Distributed computing | Conference |
ISBN | Citations | PageRank |
3-540-63631-5 | 1 | 0.40 |
References | Authors | |
8 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Juan Manuel Moreno | 1 | 186 | 32.74 |
| Jordi Madrenas | 2 | 150 | 27.87 |
| E. Alarcón | 3 | 3 | 0.93 |
| joan cabestany | 4 | 1276 | 143.82 |