How can we speed up matrix multiplication?
SIAM Review
Natural gradient works efficiently in learning
Neural Computation
Contravariant adaptation on structured matrix spaces
Signal Processing
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
The Scaling and Squaring Method for the Matrix Exponential Revisited
SIAM Journal on Matrix Analysis and Applications
Nonholonomic Orthogonal Learning Algorithms for Blind Source Separation
Neural Computation
A survey on methods for computing matrix exponentials in numerical schemes for ODEs
ICCS'03 Proceedings of the 2003 international conference on Computational science: PartII
Equivariant adaptive source separation
IEEE Transactions on Signal Processing
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This letter establishes the normalized natural gradient based algorithm in independent component analysis by employing simple matrix algebra. Moreover, another algorithm tightly related to the normalized natural gradient is introduced based on the truncated version of matrix exponentials, strictly restricting solutions in the space of non-singular matrices. Experimental results demonstrate the superior convergence of the proposed algorithms.