Blind Source Separation Algorithms with Matrix Constraints

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概要

• 論文の詳細を見る

• In many applications of Independent Component Analysis (ICA) and Blind Sourre Separation (BSS) estimated sources signals and the mixing or separating matrices have some special structure or some constraints are imposed for the matrices such as symmetries, orthogonality, non-negativity, sparseness and specified invariant norm of the separating matrix. In this paper we present several algorithms and overview some known transformations which allows us to preserve several important constraints.

• 社団法人電子情報通信学会の論文
• 2003-03-01

著者

• Cichocki A

  Lab.for Advanced Brain Signal Processing Brain Science Institute Riken

• CICHOCKI Andrzej

  Lab.for Advanced Brain Signal Processing,Brain Science Institute,RIKEN

• GEORGIEV Pando

  Lab.for Advanced Brain Signal Processing,Brain Science Institute,RIKEN

• Georgiev P

  Lab.for Advanced Brain Signal Processing Brain Science Institute Riken

• Cichocki Andrzej

  Lab.for Advanced Brain Signal Processing Brain Science Institute Riken

関連論文

• Blind Source Separation Algorithms with Matrix Constraints
• Robust Independent Component Analysis via Time-Delayed Cumulant Functions

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