029861723HOS_MIMO

所属分类:matlab编程
开发工具:matlab
文件大小:22KB
下载次数:9
上传日期:2016-11-14 12:52:00
上 传 者笑笑2015
说明:  这是一个基于高阶统计量的盲信号分离算法,便于大家参考。
(This is a higher-order statistics based on blind signal separation algorithms for easy reference.)

文件列表:
029861723HOS_MIMO\cum3equalizer.m (2618, 2002-02-10)
029861723HOS_MIMO\g_cc3_matrix.m (2188, 2002-02-10)
029861723HOS_MIMO\g_cc4_3D.m (5740, 2002-02-10)
029861723HOS_MIMO\hosmatrix.m (800, 2002-02-10)
029861723HOS_MIMO\interpolate_func.m (3959, 2002-02-10)
029861723HOS_MIMO\joint_diag.m (5114, 2000-01-16)
029861723HOS_MIMO\mimo_main.m (53410, 2002-02-10)
029861723HOS_MIMO\phase.m (531, 1998-10-13)
029861723HOS_MIMO\rec_frommag_complex.m (1071, 2002-02-10)
029861723HOS_MIMO\shadow_plot.m (976, 2002-02-10)
029861723HOS_MIMO\true_r.m (1184, 2002-02-10)
029861723HOS_MIMO (0, 2016-05-13)

Second and Higher-Order Statistics based Multiple-Input-Multiple-Output System Blind Identification Matlab Code Readme file Communications and Signal Processing Laboratory ECE Department, Drexel University Philadelphia, PA 19104, USA February, 2002 http://www.ece.drexel.edu/CSPL ---------------------------------------------------------------------------------- ---- Introduction ---- This package contains the MATLAB code for the algorithm proposed in the following papers. The file "mimo_main.m" is the implementation of the algorithm in the papers. The goal of this Matlab script is to identify a MIMO system with white inputs based on the second and higher-order statistics of the outputs only. This code will plot the blind estimation results using figures. This packages also includes some supporting functions. "rec_frommag_complex.m" is system reconstruction methods from amplitude response; "true_r.m" computes the true-correlation of the system outputs for comparison purpose only; "g_cc3_matrix.m" is an efficient MATLAB code to compute the third-order cross cumulants of three signals; "g_cc4_3D.m" is an efficient MATLAB code to compute the fourth-order cross cumulants of four signals, this code runs even faster than the correpsonding C code in PC/Windows NT platform. "joint_diag.m" is the MATLAB code written by Dr. Jean-Francois Cardoso for the implementation of his "Joint Diagonalization" method, this code is proved to be able to improve the performace the system impulse response estimation greatly; "hosmatrix.m" is the MATLAB code to generate a matrix consists of only 1 and 0 for the phase estimation method proposed in [1]. "interpolate_func.m" is the MATLAB code to interpolate a periodic function, like the FFT. It takes the advantage of the fact that FFT is periodic. It is used to interpolate the estimated V(w) at certatin frequencies where the power spectrum matries have high condition numbers. "shadow_plot.m" can plot the Monte-Carlo simulations results in a clear way where both the mean and standard deviation are shown on the plot. "cum3equalizer.m" is the implementation of Tugnait's deconvolution algorithm based on higher-order statistics for single-input single-output case. [1] Binning Chen and Athina P. Petropulu, "Frequency Domain Blind MIMO System Identification Based On Second- And Higher-Order Statistics," IEEE Transactions on Signal Processing, vol. 49(8), pp. 1677-1688, August 2001. [2] Binning Chen, Athina P. Petropulu, Lieven De Lathauwer and Bart De Moor, "Blind MIMO System Identification Based on Cross-Polyspectra," 2000 European Signal Processing Conference - EUSIPCO'2000, September 2000, Tampere, Finland. [3] Binning Chen and Athina P. Petropulu, "Multiple-Input-Multiple-Output Blind System Identification Based on Cross-Polyspectra," IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP'2000, June 2000, Istanbul, Turkey. [4] Binning Chen and Athina P. Petropulu, "Blind MIMO System Identification Based on Cross- Polyspectra," 34th Annual Conf. on Information Sciences and Systems, CISS'2000, Princeton University, March 2000. ---------------------------------------------------------------------------------- Last Updated: Sunday, February 10, 2002

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