Journal of Computational and Applied Mathematics
A delayed projection neural network for solving linear variational inequalities
IEEE Transactions on Neural Networks
An improved method for independent component analysis with reference
Digital Signal Processing
Depth estimation of face images based on the constrained ICA model
PCM'10 Proceedings of the 11th Pacific Rim conference on Advances in multimedia information processing: Part I
Content-based facial image retrieval using constrained independent component analysis
Information Sciences: an International Journal
Extracting post-nonlinear signal with reference
Computers and Electrical Engineering
A robust extraction algorithm for biomedical signals from noisy mixtures
Frontiers of Computer Science in China
One-unit second-order blind identification with reference for short transient signals
Information Sciences: an International Journal
Noisy component extraction with reference
Frontiers of Computer Science: Selected Publications from Chinese Universities
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Constrained independent component analysis (cICA) is a general framework to incorporate a priori information from problem into the negentropy contrast function as constrained terms to form an augmented Lagrangian function. In this letter, a new improved algorithm for cICA is presented through the investigation of the inequality constraints, in which different closeness measurements are compared. The utility of our proposed algorithm is demonstrated by the experiments with synthetic data and electroencephalogram (EEG) data.