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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Sadati, N. Marami, B. |
| Copyright Year | 2007 |
| Description | Author affiliation: Dept. of Electr. Eng., Sharif Univ. of Technol., Tehran (Sadati, N.; Marami, B.) |
| Abstract | In this paper, a novel approach for tuning the parameters of fuzzy wavelet systems which are used for modeling of nonlinear and complex systems is proposed. In fuzzy inference system, each fuzzy rule is analogous to a wavelet basis function multiplied by a coefficient. Using clustering techniques, the center of these basis functions are located in the detected center of clusters. In this way, not only the approximation accuracy is increased, but also the number of unknown parameters is decreased. The feasibility of the proposed method is shown by modeling two highly nonlinear functions. The comparison of the results using the proposed approach, with the previous schemes, shows the effectiveness and superiority of this algorithm. |
| Starting Page | 114 |
| Ending Page | 119 |
| File Size | 5336091 |
| Page Count | 6 |
| File Format | |
| ISBN | 1424407052 |
| DOI | 10.1109/CIDM.2007.368861 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-03-01 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Algorithm design and analysis Clustering algorithms Control system synthesis Approximation algorithms Discrete wavelet transforms Data mining Intelligent systems Computational intelligence Organizing Fuzzy systems |
| Content Type | Text |
| Resource Type | Article |
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