Processing math: 100%

一级黄色片免费播放|中国黄色视频播放片|日本三级a|可以直接考播黄片影视免费一级毛片

高級搜索

留言板

尊敬的讀者、作者、審稿人, 關(guān)于本刊的投稿、審稿、編輯和出版的任何問題, 您可以本頁添加留言。我們將盡快給您答復。謝謝您的支持!

姓名
郵箱
手機號碼
標題
留言內(nèi)容
驗證碼

基于四階累積量張量聯(lián)合對角化的多數(shù)據(jù)集聯(lián)合盲源分離

龔曉峰 毛蕾 林秋華 徐友根 劉志文

龔曉峰, 毛蕾, 林秋華, 徐友根, 劉志文. 基于四階累積量張量聯(lián)合對角化的多數(shù)據(jù)集聯(lián)合盲源分離[J]. 電子與信息學報, 2019, 41(3): 509-515. doi: 10.11999/JEIT180414
引用本文: 龔曉峰, 毛蕾, 林秋華, 徐友根, 劉志文. 基于四階累積量張量聯(lián)合對角化的多數(shù)據(jù)集聯(lián)合盲源分離[J]. 電子與信息學報, 2019, 41(3): 509-515. doi: 10.11999/JEIT180414
Xiaofeng GONG, Lei MAO, Qiuhua LIN, Yougen XU, Zhiwen LIU. Joint Blind Source Separation Based on Joint Diagonalization of Fourth-order Cumulant Tensors[J]. Journal of Electronics & Information Technology, 2019, 41(3): 509-515. doi: 10.11999/JEIT180414
Citation: Xiaofeng GONG, Lei MAO, Qiuhua LIN, Yougen XU, Zhiwen LIU. Joint Blind Source Separation Based on Joint Diagonalization of Fourth-order Cumulant Tensors[J]. Journal of Electronics & Information Technology, 2019, 41(3): 509-515. doi: 10.11999/JEIT180414

基于四階累積量張量聯(lián)合對角化的多數(shù)據(jù)集聯(lián)合盲源分離

doi: 10.11999/JEIT180414
基金項目: 國家自然科學基金面上項目(61671106, 61871067),國家自然科學基金重點項目(61331019)
詳細信息
    作者簡介:

    龔曉峰:男,1981年生,副教授,研究方向為盲信號處理、陣列信號處理

    毛蕾:女,1991年生,碩士生,研究方向為盲信號處理

    林秋華:女,1970年生,教授,研究方向為盲信號處理及其應用

    徐友根:男,1975年生,教授,研究方向為陣列信號處理及其應用

    劉志文:男,1962年生,教授,研究方向為數(shù)字信號與圖像處理及應用,嵌入式系統(tǒng)開發(fā)及應用,生物醫(yī)學信息獲取與處理

    通訊作者:

    龔曉峰 xfgong@dlut.edu.cn

  • 中圖分類號: TN911.7

Joint Blind Source Separation Based on Joint Diagonalization of Fourth-order Cumulant Tensors

Funds: The National Natural Science Foundation of China (61671106, 61871067, 61331019)
  • 摘要:

    該文提出一種基于四階累積量張量聯(lián)合對角化的聯(lián)合盲源分離(J-BSS)算法。首先通過計算4階互累積量將多數(shù)據(jù)集信號的J-BSS問題轉(zhuǎn)化為4階張量聯(lián)合對角化問題。接下來,基于雅可比連續(xù)旋轉(zhuǎn)將張量聯(lián)合對角化這類非線性優(yōu)化問題,轉(zhuǎn)化為一系列可獲取閉式解的簡單子優(yōu)化問題,并通過交替迭代對多數(shù)據(jù)集混合矩陣進行更新,進而實現(xiàn)J-BSS。實驗結(jié)果表明,所提算法具有良好的收斂性能,較之現(xiàn)有的同類型BSS及J-BSS算法具有更高的精度。此外,該算法在分離實際胎兒心電信號方面也表現(xiàn)出良好的性能。

  • 圖  1  無噪聲下JTD和GOJD的A-PI值隨掃描次數(shù)的變化曲線

    圖  2  本文算法和同類型算法在分離計算機合成信號時的性能對比

    圖  3  實際FECG信號分離實驗結(jié)果

    表  1  基于雅克比旋轉(zhuǎn)的四階張量聯(lián)合對角化算法

     輸入: K個滿足式(5)的張量T1,T2,···,TKCR×R×R×R。
     對因子矩陣進行初始化,進行如下步驟,直至收斂。
       令i從1至R1變化, ji +1至R變化,對固定索引(i, j):
       (1)根據(jù)式(16),計算矩陣˜G(m)i,j,m=1,2,3,4
       (2)根據(jù)式(10),更新矩陣˜U(m)T1,T2,···,TK。
     輸出: 4個因子矩陣估計值˜U(1),˜U(2),˜U(3),˜U(4)。
    下載: 導出CSV
  • LAHAT D, ADALI T, and JUTTEN C. Multimodal data fusion: An overview of methods, challenges, and prospects[J]. Proceedings of the IEEE, 2015, 103(9): 1449–1477. doi: 10.1109/JPROC.2015.2460697
    STEYRL D, KRAUSZ G, KOSCHUTNIG K, et al. Reference Layer Adaptive Filtering (RLAF) for EEG artifact reduction in simultaneous EEG-fMRI[J]. Journal of Neural Engineering, 2017, 14(2): 026003. doi: 10.1088/1741-2552/14/2/026003
    陳強, 陳勛, 余鳳瓊. 基于獨立向量分析的腦電信號中肌電偽跡的去除方法[J]. 電子與信息學報, 2016, 38(11): 2840–2847. doi: 10.11999/JEIT160209

    CHEN Qiang, CHEN Xun, and YU Fengqiong. Removal of muscle artifact from EEG data based on independent vector analysis[J]. Journal of Electronics &Information Technology, 2016, 38(11): 2840–2847. doi: 10.11999/JEIT160209
    KUANG Lidan, LIN Qiuhua, GONG Xiaofeng, et al. Adaptive independent vector analysis for multi-subject complex-valued fMRI data[J]. Journal of Neuroscience Methods, 2017, 281: 49–63. doi: 10.1016/j.jneumeth.2017.01.017
    付衛(wèi)紅, 張琮. 基于步長自適應的獨立向量分析卷積盲分離算法[J]. 電子與信息學報, 2018, 40(9): 2158–2164. doi: 10.11999/JEIT171156

    FU Weihong and ZHANG Cong. Independent vector analysis convolutive blind separation algorithm based on step-size adaptive[J]. Journal of Electronics &Information Technology, 2018, 40(9): 2158–2164. doi: 10.11999/JEIT171156
    GONG Xiaofeng, WANG Xiulin, and LIN Qiuhua. Generalized non-orthogonal joint diagonalization with LU decomposition and successive rotations[J]. IEEE Transactions on Signal Processing, 2015, 63(5): 1322–1334. doi: 10.1109/TSP.2015.2391074
    XING Ling, MA Qiang, and ZHU Min. Tensor semantic model for an audio classification system[J]. Science China (Information Sciences) , 2013, 56(6): 1–9. doi: 10.1007/s11432-013-4821-x
    COMON P and JUTTEN C. Handbook of Blind Source Separation: Independent Component Analysis and Applications[M]. Kidlington, UK Academic Press, Inc., 2010.
    GONG Xiaofeng, LIN Qiuhua, CONG Fengyu, et al. Double coupled canonical polyadic decomposition for joint blind source separation[J]. IEEE Transactions on Signal Processing, 2018, 66(13): 3475–3490. doi: 10.1109/TSP.2018.2830317
    LI Xilin, ADALI T, and ANDERSON M. Joint blind source separation by generalized joint diagonalization of cumulant matrices[J]. Signal Processing, 2011, 91(10): 2314–2322. doi: 10.1016/j.sigpro.2011.04.016
    MIAO Jifei, CHENG Guanghui, CAI Yufeng, et al. Approximate joint singular value decomposition algorithm based on Givens-like rotation[J]. IEEE Signal Processing Letters, 2018, 25(5): 620–624. doi: 10.1109/LSP.2018.2815584
    HAROLD H. Relations between two sets of variates[J]. Biometrika, 1936, 28(3/4): 321–377. doi: 10.2307/2333955
    DE LATHAUWER L, DE MOOR B, and VANDEWALLE J. Independent component analysis and (simultaneous) third-order tensor diagonalization[J]. IEEE Transactions on Signal Processing, 2001, 49(10): 2262–2271. doi: 10.1109/78.950782
    LIU Yingliang, GONG Xiaofeng, and LIN Qiuhua. Non-orthogonal tensor diagonalization based on successive rotations and LU decomposition[C]. IEEE International Conference on Natural Computation. Zhangjiajie, China, 2015: 102–107.
    WANG Xiulin, GONG Xiaofeng, LIN Qiuhua. A study on parallelization of successive rotation based joint diagonalization[C]. International Conference on Digital Signal Processing. Hong Kong, China, 2014: 1–5.
    CARDOSO J F and SOULOUMIAC A. Blind beamforming for non-Gaussian signals[J]. IEE Proceedings F (Radar and Signal Processing) , 1993, 140(6): 362–370. doi: 10.1049/ip-f-2.1993.0054
    LI Yiou, ADALI T, and WANG Wei, et al. Joint blind source separation by multiset canonical correlation analysis[J]. IEEE Transactions on Signal Processing, 2009, 57(10): 3918–3929. doi: 10.1109/TSP.2009.2021636
    MOOR D. Database for the identification of systems (DaISy) [OL]. http://www.esat.kuleuven.ac.be/sista/daisy, 2010.
    DE LATHAUWER L, DE MOOR B, and VANDEWALLE J. Fetal electrocardiogram extraction by blind source subspace separation[J]. IEEE Transactions on Biomedical Engineering, 2000, 47(5): 567–572. doi: 10.1109/78.950782
    CARDOSO J F. Multidimensional independent component analysis[C]. IEEE International Conference on Acoustics, Speech and Signal Processing. Seattle, USA, 1998: 1941–1944.
  • 加載中
圖(3) / 表(1)
計量
  • 文章訪問數(shù):  2816
  • HTML全文瀏覽量:  923
  • PDF下載量:  135
  • 被引次數(shù): 0
出版歷程
  • 收稿日期:  2018-05-03
  • 修回日期:  2018-10-11
  • 網(wǎng)絡出版日期:  2018-10-31
  • 刊出日期:  2019-03-01

目錄

    /

    返回文章
    返回