Title :
Multicomponent Linear FM Signal Detection Based on Support Vector Clustering
Author :
Linghuan, Wang ; Hongguang, Ma ; Qi, Li ; Zheng, Li
Author_Institution :
Res. Inst. of High Technol., Xi´´an
Abstract :
The support vector clustering (SVC) algorithm was introduced to get the number of the pinnacles in the result of the time-frequency analysis and Radon transform of the multicomponent linear FM (LFM) signal, and to fulfil the detection of the components of the LFM signal. Meanwhile, an approach called near zero mean, for reducing the point number of the input data-set for SVC, was proposed to improve the computation efficiency. And a novel cluster labeling method was developed to improve the SVC algorithm. The simulation results depict that the SVC-radon-time-frequency approach is efficient for the detection and parameter estimation of the multi-components LFM signal
Keywords :
Radon transforms; parameter estimation; pattern clustering; support vector machines; time-frequency analysis; Radon transform; SVC algorithm; cluster labeling method; multicomponent linear FM signal detection; parameter estimation; support vector clustering; time-frequency analysis; Clustering algorithms; Computational modeling; Filters; Labeling; Narrowband; Signal detection; Static VAr compensators; Time frequency analysis; Vectors; Wavelet transforms; Detection; Multicomponent LFM Signal; SVC;
Conference_Titel :
Information, Communications and Signal Processing, 2005 Fifth International Conference on
Conference_Location :
Bangkok
Print_ISBN :
0-7803-9283-3
DOI :
10.1109/ICICS.2005.1689147