|
|
|
|
| LEADER |
01595naaaa2200349uu 4500 |
| 001 |
48837 |
| 005 |
20210527 |
| 020 |
|
|
|a KSP/1000125447
|
| 020 |
|
|
|a 9783731510628
|
| 024 |
7 |
|
|a 10.5445/KSP/1000125447
|c doi
|
| 041 |
0 |
|
|h German
|
| 042 |
|
|
|a dc
|
| 100 |
1 |
|
|a Sander, Jennifer
|e auth
|
| 245 |
1 |
0 |
|a Ansätze zur lokalen Bayes'schen Fusion von Informationsbeiträgen heterogener Quellen
|
| 260 |
|
|
|a Karlsruhe
|b KIT Scientific Publishing
|c 2021
|
| 300 |
|
|
|a 1 electronic resource (342 p.)
|
| 856 |
|
|
|z Get fulltext
|u https://library.oapen.org/handle/20.500.12657/48837
|
| 506 |
0 |
|
|a Open Access
|2 star
|f Unrestricted online access
|
| 520 |
|
|
|a The solution of various tasks benefits from information fusion or even requires it. The Bayesian fusion methodology is clear, well-founded and fulfills the essential requirements for a meaningful methodology also for fusing the contributions of heterogeneous information sources. In many practically relevant tasks, Bayesian methods cause high, often unacceptable effort. In the work, novel approaches to cope with Bayesian fusion in such situations are formulated and investigated.
|
| 540 |
|
|
|a Creative Commons
|
| 546 |
|
|
|a German
|
| 650 |
|
7 |
|a Maths for computer scientists
|2 bicssc
|
| 653 |
|
|
|a Informationsfusion
|
| 653 |
|
|
|a heterogene Informationsquellen
|
| 653 |
|
|
|a Bayes'sche Theorie
|
| 653 |
|
|
|a Prinzip der Maximalen Entropie
|
| 653 |
|
|
|a Unsicherheit
|
| 653 |
|
|
|a information fusion
|
| 653 |
|
|
|a heterogeneous information sources
|
| 653 |
|
|
|a Bayesian theory
|
| 653 |
|
|
|a Maximum Entropy principle
|
| 653 |
|
|
|a uncertainty
|
