Using Fuzzy Logic to Enhance Classification of Human Motion Primitives

Author(s):  
Barbara Bruno ◽  
Fulvio Mastrogiovanni ◽  
Alessandro Saffiotti ◽  
Antonio Sgorbissa
Author(s):  
Arjon Turnip ◽  
Gilbert F. Y. Sihombing ◽  
Giraldo F. J. Sihombing ◽  
George Michael Tampubolon ◽  
Peri Turnip ◽  
...  
Keyword(s):  

2020 ◽  
Vol 13 (2) ◽  
pp. 537-551
Author(s):  
Shuai Zhang ◽  
Xingyou Huang ◽  
Jinzhong Min ◽  
Zhigang Chu ◽  
Xiaoran Zhuang ◽  
...  

Abstract. To obtain better performance of meteorological applications, it is necessary to distinguish radar echoes from meteorological and non-meteorological targets. After a comprehensive analysis of the computational efficiency and radar system characteristics, we propose a fuzzy logic method that is similar to the MetSignal algorithm; the performance of this method is improved significantly in weak-signal regions where polarimetric variables are severely affected by noise. In addition, post-processing is adjusted to prevent anomalous propagation at a far range from being misclassified as meteorological echo. Moreover, an additional fuzzy logic echo classifier is incorporated into post-processing to suppress misclassification in the melting layer. An independent test set is selected to evaluate algorithm performance, and the statistical results show an improvement in the algorithm performance, especially with respect to the classification of meteorological echoes in weak-signal regions.


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