A Survey of The Performance Indexes of ICA Algorithms

Ali MANSOUR 1  Mitsuru Kawamoto 2 & Noboru OHNISHI 3
1- ENSIETA, 29806 Brest cedex 09 (FRANCE).
2- Dept. of Electronic and Control Systems Eng., Shimane University, Shimane 690-8504, (JAPAN)
\normalsize 3- Bio-Mimetic Control Research Center (RIKEN), Nagoya 463-003 (JAPAN)

abstract
This paper deals with the problem of blind separation of sources (BSS).
 In the literature, one can find many Independent Component Algorithms
 (ICA) to solve the BSS. To demonstrate the performances of their algorithms,
 researchers often use different methods or performance indexes depending on their
 source signals and their applications. Many methods and performance indexes can not
 be used to compare two different algorithms applied to different signals. Most of the
  widely used performance indexes or methods are mentioned and discussed hereafter. We
  also give many examples to show limitations or drawbacks of some performance indexes or methods.

keywords: Blind Separation of Sources, BSS,  ICA, Crosstalk, SNR, SINR, Gap or Distance
to Diagonal Matrix, Performance Indexes, Crosstalk Error, Rejection Level, Global Index,
Symbol Error Rate, Scatter Plot, Error Signals, Real World Applications.