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Description: 本文提出一种基于增广拉格朗日法的非线性约束优化算法用于独立成份分析(ICA), 仿真试验结果表明此方法可以有效的用于独立成份的分离. -This paper presents a broad-based increase Lagrange method of nonlinear constrained optimization algorithm for the independent component analysis (ICA), the simulation results show that this method can be effective for the separation of independent components.
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Size: 89798 |
Author: 周周 |
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Description: 本文提出一种基于增广拉格朗日法的非线性约束优化算法用于独立成份分析(ICA), 仿真试验结果表明此方法可以有效的用于独立成份的分离. -This paper presents a broad-based increase Lagrange method of nonlinear constrained optimization algorithm for the independent component analysis (ICA), the simulation results show that this method can be effective for the separation of independent components.
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Size: 89088 |
Author: 周周 |
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Description: We present the technique of the ICA with Reference (ICA-R) to extract an interesting subset of independent sources from their linear
mixtures when some a priori information of the sources are available in the form of rough templates (references). The constrained
independent component analysis (cICA) is extended to incorporate the reference signals that carry some information of the sources as
additional constraints into the ICA contrast function. A neural algorithm is then proposed using a Newton-like approach to obtain an
optimal solution to the constrained optimization problem. Stability of the convergence and selection of parameters in the learning
algorithm are analyzed. Experiments with synthetic signals and real fMRI data demonstrate the efficacy and accuracy of the proposed
algorithm.
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Size: 390144 |
Author: ma ming |
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Description: cICA code for the constrained ICA algorithm
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Size: 669696 |
Author: 胡理 |
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