Title :
SVC & K-Means and Type-Entropy Based De-Interleaving/Recognition System of Radar Pulses
Author :
Guo, Qiang ; Zhang, Xingzhou ; Li, Zheng
Author_Institution :
Coll. of Inf. & Commun. Eng., Harbin Eng. Univ.
Abstract :
First, the paper shows a novel de-interleaving method based on support vector clustering (SVC) and K-means clustering. Secondly, it presents a notion of type-entropy and the recognition technology based on type-entropy is introduced into de-interleaving system so that a novel joint de-interleaving/recognition system of radar pulse sequence is to be presented. The simulation experiment result shows that the system can sort efficiently radar signals in the high density and complex pulses environment
Keywords :
entropy; pattern clustering; radar signal processing; support vector machines; K-means clustering; SVC; joint deinterleaving-recognition system; radar pulse sequence; support vector clustering; type-entropy; Data processing; Educational institutions; Electromagnetic measurements; Entropy; Histograms; Radar; Radio frequency; Signal processing; Sorting; Static VAr compensators; K-Means; SVC; de-interleaving; recognition; type-entropy;
Conference_Titel :
Information Acquisition, 2006 IEEE International Conference on
Conference_Location :
Weihai
Print_ISBN :
1-4244-0528-9
Electronic_ISBN :
1-4244-0529-7
DOI :
10.1109/ICIA.2006.305821
