| 000 | 01044camuu22003014a 4500 | |
| 001 | 000000769218 | |
| 005 | 20020610095248 | |
| 008 | 010718s2001 maua b 001 0 eng | |
| 010 | ▼a 01038476 | |
| 015 | ▼a GBA1-V1865 | |
| 020 | ▼a 0792375033 (alk. paper) | |
| 040 | ▼a DLC ▼c DLC ▼d UKM ▼d C#P ▼d OHX ▼d 211009 | |
| 042 | ▼a pcc | |
| 049 | 1 | ▼l 121063329 ▼f 과학 |
| 050 | 0 0 | ▼a Q327 ▼b .A57 2001 |
| 072 | 7 | ▼a Q ▼2 lcco |
| 082 | 0 0 | ▼a 006.4 ▼2 21 |
| 090 | ▼a 006.4 ▼b A593d | |
| 100 | 1 | ▼a Angstenberger, Larisa. |
| 245 | 1 0 | ▼a Dynamic fuzzy pattern recognition with applications to finance and engineering / ▼c Larisa Angstenberger. |
| 260 | ▼a Boston : ▼b Kluwer Academic, ▼c c2001. | |
| 300 | ▼a xxii, 287 p. : ▼b ill. ; ▼c 25 cm. | |
| 440 | 0 | ▼a International series in intelligent technologies ; ▼v 17 |
| 504 | ▼a Includes bibliographical references (p. [269]-277) and index. | |
| 650 | 0 | ▼a Pattern perception. |
| 650 | 0 | ▼a Fuzzy systems. |
| 938 | ▼a Otto Harrassowitz ▼b HARR ▼n har015034455 ▼c 284.00 DEM |
소장정보
| No. | 소장처 | 청구기호 | 등록번호 | 도서상태 | 반납예정일 | 예약 | 서비스 |
|---|---|---|---|---|---|---|---|
| No. 1 | 소장처 과학도서관/Sci-Info(2층서고)/ | 청구기호 006.4 A593d | 등록번호 121063329 | 도서상태 대출가능 | 반납예정일 | 예약 | 서비스 |
컨텐츠정보
책소개
Dynamic Fuzzy Pattern Recognition with Applications to Finance and Engineering focuses on fuzzy clustering methods which have proven to be very powerful in pattern recognition and considers the entire process of dynamic pattern recognition. This book sets a general framework for Dynamic Pattern Recognition, describing in detail the monitoring process using fuzzy tools and the adaptation process in which the classifiers have to be adapted, using the observations of the dynamic process. It then focuses on the problem of a changing cluster structure (new clusters, merging of clusters, splitting of clusters and the detection of gradual changes in the cluster structure). Finally, the book integrates these parts into a complete algorithm for dynamic fuzzy classifier design and classification.
Dynamic Fuzzy Pattern Recognition with Applications to Finance and Engineering focuses on fuzzy clustering methods which have proven to be very powerful in pattern recognition and considers the entire process of dynamic pattern recognition. This book sets a general framework for Dynamic Pattern Recognition, describing in detail the monitoring process using fuzzy tools and the adaptation process in which the classifiers have to be adapted, using the observations of the dynamic process. It then focuses on the problem of a changing cluster structure (new clusters, merging of clusters, splitting of clusters and the detection of gradual changes in the cluster structure). Finally, the book integrates these parts into a complete algorithm for dynamic fuzzy classifier design and classification.
정보제공 :
목차
Foreword. Acknowledgements. 1. Introduction. 2. General Framework of Dynamic Pattern Recognition. 3. Stages of the Dynamic Pattern Recognition Process. 4. Dynamic Fuzzy Classifier Design with Point-Prototype Based Clustering Algorithms. 5. Similarity Concepts for Dynamic Objects in Pattern Recognition. 6. Applications of Dynamic Pattern Recognition Methods. 7. Conclusions. References.
정보제공 :