You have requested a machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Neither SPIE nor the owners and publishers of the content make, and they explicitly disclaim, any express or implied representations or warranties of any kind, including, without limitation, representations and warranties as to the functionality of the translation feature or the accuracy or completeness of the translations.
Translations are not retained in our system. Your use of this feature and the translations is subject to all use restrictions contained in the Terms and Conditions of Use of the SPIE website.
3 September 1993MLANS application to sensor fusion
Fusion of information from multiple sources is an increasingly important area of research and application. This problem is often complicated by various sensors having different limitations and fields of view. Further complications result from the absence of prior knowledge. in addition to fusing diverse information, it is also necessary to manage multiple sensors with various limitations efficiently for optimal overall system performance. We have solved this set of problems using the MLANS neural network that employs model based approach and fuzzy decision logic.
The alert did not successfully save. Please try again later.
Leonid I. Perlovsky, "MLANS application to sensor fusion," Proc. SPIE 1955, Signal Processing, Sensor Fusion, and Target Recognition II, (3 September 1993); https://doi.org/10.1117/12.155000