Impact of higher-order statistics on adaptive algorithms for blind source separation
作者： C.C. Cavalcante , J.M.T. Romano
DOI: 10.1109/SPAWC.2004.1439226
关键词:
摘要: The paper is devoted to present an analysis of the impact higher order statistics (HOS) in adaptive blind source separation criteria. Despite well known fact that they are necessary provide a general framework, their on performance solutions still open research field. approach probability density function (pdf) recovering used. In verify analysis, two constrained algorithms investigated. Namely, multiuser kurtosis algorithm (MUK) and fitting (MU-CFPA) used due desired characteristics different HOS involved design. Simulation results carried out basis our analysis.
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