1- https://doi.org/10.1007/1-4020-3432-6_36
A Comparison of ICA Algorithms in Biomedical Signal Processing
- Jan 1, 2005
- B Azzerboni +4 more
In the last years Independent Component Analysis (ICA) has been applied with success in signal processing and many algorithms have been developed in order to perform ICA. In this paper we review some algorithms, like INFOMAX (Bell and Sejnowski 1995), extended-INFOMAX (Lee, Girolami and Sejniowski 1997), FastICA (OjA, and Hyvarinen 1999), that solve the ICA problem under the assumption of the linear mixture model. We also show an overview of the nonlinear ICA algorithms and we discuss the MISEP (Almeida 2003). In order to test the performances of the reviewed algorithms, we present some applications of ICA in biomedical signal processing. In particular the application of ICA to the electroencephalographic (EEG) and surface electromyographic (sEMG) recordings are shown.
- # Independent Component Analysis
- # Biomedical Signal Processing
- # Application Of Independent Component Analysis
- # Independent Component Analysis Algorithms
- # Surface Electromyographic Recordings
- # sEMG Recordings
- # Signal Processing
- # Signal Processing Algorithms
- # Electromyographic Recordings
- # Electroencephalographic Recordings
