Welcome to the InfoSci Platform
Reference Hub1
A Novel Research in Low Altitude Acoustic Target Recognition Based on HMM

A Novel Research in Low Altitude Acoustic Target Recognition Based on HMM

Hui Liu, Wei Wang, Chuang Wen Wang
Copyright: © 2021 |Volume: 12 |Issue: 2 |Pages: 12
ISSN: 1947-8534|EISSN: 1947-8542|EISBN13: 9781799860495|DOI: 10.4018/IJMDEM.2021040102
Cite Article Cite Article

MLA

Liu, Hui, et al. "A Novel Research in Low Altitude Acoustic Target Recognition Based on HMM." IJMDEM vol.12, no.2 2021: pp.19-30. http://doi.org/10.4018/IJMDEM.2021040102

APA

Liu, H., Wang, W., & Wang, C. W. (2021). A Novel Research in Low Altitude Acoustic Target Recognition Based on HMM. International Journal of Multimedia Data Engineering and Management (IJMDEM), 12(2), 19-30. http://doi.org/10.4018/IJMDEM.2021040102

Chicago

Liu, Hui, Wei Wang, and Chuang Wen Wang. "A Novel Research in Low Altitude Acoustic Target Recognition Based on HMM," International Journal of Multimedia Data Engineering and Management (IJMDEM) 12, no.2: 19-30. http://doi.org/10.4018/IJMDEM.2021040102

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

This paper introduces an improved HMM (hidden Markov model) for low altitude acoustic target recognition. To overcome the limitation of the classical CDHMM (continuous density hidden Markov model) training algorithm and the generalization ability deficiency of existing discriminative learning methods, a new discriminative training method for estimating the CDHMM in acoustic target recognition is proposed based on the principle of maximizing the minimum relative separation margin. According to the definition of the relative margin, the new training criterion can be equation as a standard constrained minimax optimization problem. Then, the optimization problem can be solved by a GPD (generalized probabilistic descent) algorithm. The experimental results show that the performance of the algorithm is significantly improved compared with the former training method, which can effectively improve the recognition ability of the acoustic target recognition system.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.