An algebraic solution to independent component analysis

The independent component analysis (ICA) is the technique of extracting original signals from many independent sources without a priori information on the sources and the mixing process. We proposed a novel algebraic solution to ICA. Independent components are recovered by solving simultaneous equations derived from the definition of the independence. The proposed algorithm is evaluated by an experiment where original images are extracted from mixed images. The reduction of the processing time is achieved with the comparable levels of accuracy to conventional algorithms.

[1]  Kazuyoshi Itoh,et al.  Independent component analysis by transforming a scatter diagram of mixtures of signals , 2000 .

[2]  Shun-ichi Amari,et al.  Adaptive Online Learning Algorithms for Blind Separation: Maximum Entropy and Minimum Mutual Information , 1997, Neural Computation.

[3]  Erkki Oja,et al.  A class of neural networks for independent component analysis , 1997, IEEE Trans. Neural Networks.

[4]  Nathalie Delfosse,et al.  Adaptive blind separation of independent sources: A deflation approach , 1995, Signal Process..

[5]  Gilles Burel,et al.  Blind separation of sources: A nonlinear neural algorithm , 1992, Neural Networks.

[6]  Norimichi Tsumura,et al.  Independent Component Analysis of Skin Color Image , 1998, CIC.

[7]  Kenneth J. Pope,et al.  Blind Signal Separation II. Linear, Convolutive Combinations: II. Linear, Convolutive Combinations , 1996, Digit. Signal Process..

[8]  Kenneth J. Pope,et al.  Blind Signal Separation I. Linear, Instantaneous Combinations: I. Linear, Instantaneous Combinations , 1996, Digit. Signal Process..

[9]  Andrew D. Back,et al.  A First Application of Independent Component Analysis to Extracting Structure from Stock Returns , 1997, Int. J. Neural Syst..

[10]  R N Vigário,et al.  Extraction of ocular artefacts from EEG using independent component analysis. , 1997, Electroencephalography and clinical neurophysiology.

[11]  W. S. Miller.  Variation of IQ's obtained from group tests. , 1933 .

[12]  Kazuya Takeda,et al.  Blind signal separation for recognizing overlapped speech. , 1998 .

[13]  Aapo Hyvärinen,et al.  A Fast Fixed-Point Algorithm for Independent Component Analysis , 1997, Neural Computation.

[14]  Christian Jutten,et al.  Blind separation of sources, part I: An adaptive algorithm based on neuromimetic architecture , 1991, Signal Process..

[15]  Pierre Comon,et al.  Independent component analysis, A new concept? , 1994, Signal Process..

[16]  Jc Dainty,et al.  PROBABILITY, STATISTICAL OPTICS AND DATA TESTING - A PROBLEM-SOLVING APPROACH - FRIEDEN,BR , 1983 .