A survey of the performance indexes of ICA algorithms

Ali Mansour (1) , Mitsuru Kawamoto (2) , Ohnishi Noboru (3)

1 Lab-STICC_ENSTAB_CACS_COM
2 AIST - Advanced Industrial Science and technology
3 Biological Information Engineering Laboratory

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.

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Ali Mansour, Mitsuru Kawamoto, Ohnishi Noboru. A survey of the performance indexes of ICA algorithms. International Conference on Modelling, Identification and Control (MIC 2002), Feb 2002, Innsburk, Austria. ⟨hal-00802771⟩