HE Xuansen, WANG Fang, CHAI Wenbiao, et al., “Ant Colony Clustering Algorithm for Underdetermined BSS,” Chinese Journal of Electronics, vol. 22, no. 2, pp. 319-324, 2013,
Citation: HE Xuansen, WANG Fang, CHAI Wenbiao, et al., “Ant Colony Clustering Algorithm for Underdetermined BSS,” Chinese Journal of Electronics, vol. 22, no. 2, pp. 319-324, 2013,

Ant Colony Clustering Algorithm for Underdetermined BSS

Funds:  This work is supported by the National Natural Science Foundation of China (No.61072122) and the Key Project of Hunan Provincial Natural Science Foundation (No.11JJ20153).
  • Received Date: 2011-12-01
  • Rev Recd Date: 2012-03-01
  • Publish Date: 2013-04-25
  • In underdetermined blind source separation, in order to quickly and accurately estimate the mixing matrix and the source signals, this paper presents a new algorithm based on ant colony clustering. The basic ideal of the algorithm is that we utilize the linear clustering characteristic of sparse signals to estimate the number of sources and the column vector of the mixing matrix by estimating the directions of the straight lines. In the preprocessing step, the observed signals in time domain are transformed to sparse signals in frequency domain. Through normalizing the observed data the linearity clustering is translated to compact clustering, and then using ant colony clustering to get the number of source signals and the mixing matrix. Finally, based on the estimation of the mixing matrix, the source signals are recovered by linear programming method. The simulation results illustrate the availability and accuracy of the proposed algorithm.
  • loading
  • J.F. Cardoso, "Blind signal separation: statistical principles", Proceedings of IEEE, Vol.41, No.10, pp.2009-2025, 1998.
    S. Choi, A. Cichocki, H.M. Park et al., "Blind source separation and independent component analysis: A review", Neural Information Processing-Letters and Reviews, Vol.6, No.1, pp.1-57, 2005.
    P. Comon, C. Jutten, "Handbook of blind source separation", Academic Press is an imprint of Elsevier, 2010.
    P. Bofill, M. Zibulevsky, Underdetermined blind source separation using sparse representations", Signal Processing, Vol.81, pp.2353-2362, 2001.
    Y.Q. Li, A. Cichocki, S. Amari, "Analysis of sparse representation and blind source separation", Neural Computation, Vol.16, No.6, pp.1193-1234, 2004.
    T.Y. Sun, L.E. Lan, C.C. Liu et al., "Mixing matrix identification for underdetermined blind signal separation: Using hough transform and fuzzy k-means clustering", Proc. of the 2009 IEEE International Conference on Systems, Man, and Cybernetics, San Antonio, USA, pp.1621-1626, 2009.
    Y.Q. Li, S. Amari, A. Cichocki et al., "Underdetermined blind source separation based on sparse representation", IEEE Trans. on Signal Processing, Vol.54, No.2, pp.423-437, 2006.
    P. Bofill, "Underdetermined blind separation of delayed sound sources in the frequency domain", Neurocomputing, Vol.55, pp.627-641, 2002.
    O. Yilmaz, S. Rickard, "Blind separation of speech mixtures via time-frequency masking", IEEE Trans. on Signal Processing, Vol.52, No.7, pp.1830-1847, 2004.
    Z.S. He, S.L. Xie, Y.L. Fu, "Sparse representation and blind source separation of ill-posed mixtures", Science in China Series F: Information Sciences, Vol.49, No.5, pp.639-652, 2006.
    M. Dorigo, G.D. Caro, L.M. Gambardella, "Ant algorithms for discrete optimization", Proc. of the Congress on E.C., 1999.
    M. Dorigo, C. Blum, "Ant colony optimization theory: a survey", Theoretical Computer Science, Vol.344, pp.243-278, 2005.
    Y.F. Han, P.F. Shi, "An improved ant colony algorithm for fuzzy clustering in image segmentation", Neurocomputing, Vol.70, pp.665-671, 2007.
  • 加载中


    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (546) PDF downloads(1216) Cited by()
    Proportional views


    DownLoad:  Full-Size Img  PowerPoint