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Maximum Likelihood Based Quantum Set Separation

  • Sándor Imre
  • Ferenc Balázs
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3036)

Abstract

In this paper we introduce a method, which is used for set separation based on quantum computation. In case of no a-priori knowledge about the source signal distribution, it is a challenging task to find an optimal decision rule which could be implemented in the separating algorithm. We lean on the Maximum Likelihood approach and build a bridge between this method and quantum counting. The proposed method is also able to distinguish between disjunct sets and intersection sets.

Keywords

Quantum Search Optimal Decision Rule Conditional Probability Density Function Quantum Search Algorithm Separation Decision 
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 2004

Authors and Affiliations

  • Sándor Imre
    • 1
  • Ferenc Balázs
    • 1
  1. 1.Mobile Communications & Computing Laboratory, Department of TelecommunicationsBudapest University of Technology and EconomicsBudapestHungary

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