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Optimum Data Quantization in Signal Detection

  • Saleem A. Kassam

Abstract

The need to use quantized data in signal detection can arise in many situations. If remotely acquired data is to be transmitted to a central processing facility, for example, data rate reduction may be highly desirable or necessary. Similarly, storage of data for off-line processing may also require quantization into a relatively small number of levels, especially if one is dealing with a large volume of data. The use of quantized data often results in more robust This work was supported by the Air Force Office of Scientific Research under Grant AFOSR 82-0022. systems which are not very sensitive in their performance to deviations of the actual noise density functions from those assumed in their design. Finally, the use of quantized data can allow simple adaptive schemes to be implemented to allow the system to retain good detection performance even when the noise characteristics can vary considerably over time.

Keywords

Locally Optimum Output Level Minimum Mean Square Error Asymptotically Optimum Optimum Quantization 
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 New York Inc. 1986

Authors and Affiliations

  • Saleem A. Kassam
    • 1
  1. 1.Department of Electrical EngineeringUniversity of PennsylvaniaPhiladephiaUSA

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