High-Order Contrasts for Independent Component Analysis

Neural Computation - Tập 11 Số 1 - Trang 157-192 - 1999
J.-F. Cardoso1
1Ecole Nationale Supérieure des Télécommunications, 75634 Paris Cedex 13, France

Tóm tắt

This article considers high-order measures of independence for the independent component analysis problem and discusses the class of Jacobi algorithms for their optimization. Several implementations are discussed. We compare the proposed approaches with gradient-based techniques from the algorithmic point of view and also on a set of biomedical data.

Từ khóa


Tài liệu tham khảo

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Thông tin xuất bản

Neural Computation

Tập 11 Số 1

157-192

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