Earticle

초록

영어

Mixing matrix estimation (MME) algorithm was proposed for the mixing matrix estimation problem of underdetermined blind source separation. The algorithm is based on a combination of processing of isolated time–frequency points from local directional density detection and Hough transform (HT). Firstly, signal sparsity was strengthened through the processing of single-source time–frequency points in the transform domain. Next, HT was applied to the directional straight lines in the scatter plot and realized the spatial transformation. The number of source signals and mixing matrix were estimated by determining the local maxima of cumulative array. To deal with the peak values clustering issue that commonly arises with HT, the local directional density detection method was used to identify and eliminate isolated time–frequency points. HT was then used to improve the accuracy of MME. The experimental results indicate that the proposed method is able to achieve MME under the condition when the number of source signals is unknown. Further, the accuracy of estimation is better than other commonly-used methods such as K-means.

목차

Abstract
 1. Introduction
 2. Signal Sparsity Strengthen based on Single-source Time–frequency Points Processing
 3. Mixing Matrix Estimation based on Isolated Points Detection and HT
  3.1 Directional Straight Line Transformation based on HT
  3.2. Mixing Matrix Estimation based on Isolated Points Detection
 4. Results and Analysis
  4.1. Results and Analysis of Experiment 1
  4.2. Results and Analysis of Experiment 2
 5. Conclusion
 Acknowledgements
 Reference

키워드

저자

• SUN Jie-Di [ School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China ]
• LI Yu-Xia [ School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China ]
• WEN Jiang-Tao [ Key Laboratory of Measurement Technology and Instrumentation of HeBei Province, Yanshan University, Qinhuangdao, 066004, China) ]
• YAN Sheng-Nan [ School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605