Toshinao Akuzawa

As extensions to the strict method developed in [1], varia­ tions of the Newton method for the independent component analysis(ICA) are proposed. Our method presented here is highly practical and simple. Concrete merits of our algo­ rithm are as follows. i) Robust under gaussian noises. In the presence of strong gaussian noises it outperforms the ex­ isting methods like the JADE[2] and the FICA[3]. ii) By two deformations it becomes considerably stable globally. Although the first deformation is apparently unnatural, a justification is given based on the random matrix arguments. iii) Each step of the methods proposed here resolves itself into the determination of the inverse of 2  2 matrices or generalized inverse matrices of 3  2 matrices. There is no need to deal with gigantic matrices and little computational resources are required.