A Novel Feature Extraction Algorithm of Acoustic Targets Based on Locality Preserving Discriminant Projections
This paper proposes a new supervised manifold learning algorithm called locality preserving discriminant projections (LPDP) to solve the problem of poor robustness in acoustic targets recognition. The algorithm is based on locality preserving projections (LPP) and the method called modified maximum margin criterion (MMMC) which is adopted to explore the optimal linear transformation for translation and reseating automatically. So the proposed algorithm can not only achieve good results in classification, but also solve the small sample size problem and has the ability of out-of-sample learning. Many experiments are carried out with public databases to test the algorithm. Experiment results show that the proposed algorithm is more precise and stable than others.
acoustic target recognition locality preserving projections modified maximum margin criterion
Wang Yi Yang Jun-an Liu Hui
Electronic Engineering Institute, Hefei, Anhui, 230037 China Key Laboratory of Electronic Restriction of Anhui Province, Hefei, Anhui, 230037 China
国际会议
太原
英文
597-601
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）