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Cross-Entropy Optimization for Independent Process Analysis

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3889)

Abstract

We treat the problem of searching for hidden multi-dimensional independent auto-regressive processes. First, we transform the problem to Independent Subspace Analysis (ISA). Our main contribution concerns ISA. We show that under certain conditions, ISA is equivalent to a combinatorial optimization problem. For the solution of this optimization we apply the cross-entropy method. Numerical simulations indicate that the cross-entropy method can provide considerable improvements over other state-of-the-art methods.

Keywords

Independent Component Analysis Travelling Salesman Problem Independent Component Analysis Blind Source Separation Permutation Matrix 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  1. 1.Department of Information SystemsEötvös Loránd UniversityBudapestHungary
  2. 2.Research Group on Intelligent Information SystemsHungarian Academy of Sciences 

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