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JnS_JADE-and-SHIBBS

于 2011-02-23 发布文件大小:43KB

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代码说明：

说明：盲源信号分离的Matlab程序，包括JADE and SHIBBS两种，效果不错！(Two batch cumulant-based ICA algorithms: JADE and SHIBBS)

文件列表：

JnS_JADE and SHIBBS
...................\JnS-1.2
...................\.......\htm" target=_blank>0_README,2003,2002-06-05
...................\.......\htm" target=_blank>COPYING,18748,1999-12-22
...................\.......\Gateway.c,1541,2002-06-05
...................\.......\htm" target=_blank>History,253,2002-06-05
...................\.......\JadeR.c,120,1999-01-23
...................\.......\jadeR.m,11337,1999-01-23
...................\.......\JnS.c,16235,2002-06-05
...................\.......\JnS.h,1526,1999-01-28
...................\.......\JointDiag.c,1556,2002-06-05
...................\.......\Makefile,722,1999-01-29
...................\.......\Matutil.c,3215,1999-01-24
...................\.......\Matutil.h,523,1999-01-24
...................\.......\shibbs.m,5263,1999-01-23
...................\.......\ShibbsR.c,127,1999-01-26
...................\.......\testJnS,19212,2002-06-05
...................\.......\testJnS.c,2469,1999-01-29
...................\.......\testJnS.m,1477,1999-01-29
...................\.......\testJointDiag.m,643,1999-01-29
...................\.......\说明.txt,1325,2010-12-20
...................\.......\迷茫的时候看看(2).doc,28160,2010-11-12

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yanchixiangjia
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2012-11-01 21:51:23下载

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信号稀疏表示是一种新兴的信号分析和综合方法，其目的就是在过完备字典中用尽可能少的原子来表示信号。采用时频原子字典的信号稀疏表示能够有效地揭示非平稳信号的时变特征。信号稀疏表示吸引了研究者的大量关注，这种方法已经被应用到信号处理的许多方面，例如非平稳信号分析，信号编码、识别与信号去噪等。(Signal sparse representation is a new method of signal analysis and synthesis, and its purpose is in over-complete dictionary of atoms using as little as possible to represent the signal. When using frequency atom dictionary signal sparse representation can effectively reveal the time-varying characteristics of non-stationary signals. Signal sparse representation attracted a lot of attention of researchers, this method has been applied to many aspects of signal processing, such as non-stationary signal analysis, signal encoding, recognition and signal denoising.)

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混响研究大牛Douglas A. Abraham的经典非锐利分布混响仿真，注释很详细。(Douglas A. Abraham, Daniel reverberation study classical Non-Rayleigh Reverberation , comment in detail.)

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