A source adaptive independent component analysis algorithm through solving the estimating equation
Expert Systems with Applications: An International Journal
Blind separation of piecewise stationary non-Gaussian sources
Signal Processing
Source separation applied to heartbeat Doppler radar
SIP '07 Proceedings of the Ninth IASTED International Conference on Signal and Image Processing
IEEE Transactions on Neural Networks
Resolution enhancement in ΣΔ learners for superresolution source separation
IEEE Transactions on Signal Processing
A complex generalized Gaussian distribution: characterization, generation, and estimation
IEEE Transactions on Signal Processing
Speed and accuracy enhancement of linear ICA techniques using rational nonlinear functions
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Blind instantaneous noisy mixture separation with best interference-plus-noise rejection
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Statistical analysis of sample-size effects in ICA
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
Complex independent component analysis by entropy bound minimization
IEEE Transactions on Circuits and Systems Part I: Regular Papers
Independent component analysis by entropy bound minimization
IEEE Transactions on Signal Processing
Adaptive independent component analysis by modified Kernel density estimation
ICIC'10 Proceedings of the 6th international conference on Advanced intelligent computing theories and applications: intelligent computing
Nonorthogonal independent vector analysis using multivariate Gaussian model
LVA/ICA'10 Proceedings of the 9th international conference on Latent variable analysis and signal separation
LVA/ICA'10 Proceedings of the 9th international conference on Latent variable analysis and signal separation
A comparative study of ICA algorithms for ECG signal processing
ACAI '11 Proceedings of the International Conference on Advances in Computing and Artificial Intelligence
An automatic method for holter ECG denoising using ICA
Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies
LVA/ICA'12 Proceedings of the 10th international conference on Latent Variable Analysis and Signal Separation
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FastICA is one of the most popular algorithms for independent component analysis (ICA), demixing a set of statistically independent sources that have been mixed linearly. A key question is how accurate the method is for finite data samples. We propose an improved version of the FastICA algorithm which is asymptotically efficient, i.e., its accuracy given by the residual error variance attains the Cramer-Rao lower bound (CRB). The error is thus as small as possible. This result is rigorously proven under the assumption that the probability distribution of the independent signal components belongs to the class of generalized Gaussian (GG) distributions with parameter alpha, denoted GG(alpha) for alpha>2. We name the algorithm efficient FastICA (EFICA). Computational complexity of a Matlab implementation of the algorithm is shown to be only slightly (about three times) higher than that of the standard symmetric FastICA. Simulations corroborate these claims and show superior performance of the algorithm compared with algorithm JADE of Cardoso and Souloumiac and nonparametric ICA of Boscolo on separating sources with distribution GG(alpha) with arbitrary alpha, as well as on sources with bimodal distribution, and a good performance in separating linearly mixed speech signals