Search - ica in cdma

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[matlab] ICA_demo_fMRI DL : 0: ICA can be used in brain activation studies to reduce the number of dimension and filter out independent and interesting activations. This demonstration shows two studies. One provided by Hvidovre Universitets Hospital, Denmark, that consists of fMRI scannings of humans. Another provided by the EU sponsored MAPAWAMO project from fMRI scannings of monkeys. In the demo comparison between icaMS, icaML, icaMF, icaMF (positive sources) and PCA can be made. More detailes can found in [2]. -ICA can be used in brain activation studies to reduce the number of dimension and filter out independent and interesting activations. This demonstration shows two studies. One provided by Hvidovre Universitets Hospital, Denmark, that consists of fMRI scannings of humans. Another provided by the EU sponsored MAPAWAMO project from fMRI scannings of monkeys. In the demo comparison between icaMS, icaML, icaMF, icaMF (positive sources) and PCA can be made. More detailes can found in [2].
Update : 2025-04-04 Size : 2.64mb Publisher : 海心
[Other] ICA_algorithms_based_on_different_objective_functi DL : 1: 一共包含了5个ICA的算法，其中： fastica.m文件中的ICA算法是基于负熵的； m_fastica.m文件中的ICA算法是基于负熵的改进算法； fastica_kurt.m文件中的ICA算法是基于峭度的； fastica_ML.m文件中的ICA算法是基于互信息的； NLPCA.m文件中的ICA算法是基于非线性PCA的。-Contains a total of five ICA algorithm, in which: fastica.m file in the ICA algorithm is based on negative entropy m_fastica.m file in the ICA algorithm is based on negative entropy of the improved algorithm fastica_kurt.m file in the ICA algorithm is Based on Kurtosis fastica_ML.m file in the ICA algorithm is based on mutual information NLPCA.m file in the ICA algorithm is based on nonlinear PCA' s.
Update : 2025-04-04 Size : 5kb Publisher : nifeng
[Program doc] Ristaniemi276-00 DL : 0: Advanced ICA-Based Receivers for DS-CDMA Systems
Update : 2025-04-04 Size : 509kb Publisher : Moncef
[Communication] ICA_for_Multi_User_Detection_in_CDMA_system DL : 0: Blind Source Seperation (BSS) now is a important technology. Independent Component Analysis (ICA) is the main technique of BSS. Suppose we mix many non-Gausse signal sources,ICA can seperate the mixed signal to orignal signals without any information. This Matlab Code simulate the using ICA for Multi User Detection (MUD) in CDMA system. We demo the CDMA system with 30 Users, and use ICA seperate the signal of each user at Base Transmit Station (BTS) with the only 30 Users signal.
Update : 2025-04-04 Size : 4.1mb Publisher : Tuyen