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Compound Poisson-Processes

  • Donald L. Snyder
  • Michael I. Miller
Part of the Springer Texts in Electrical Engineering book series (STELE)

Abstract

One motivation for the model we develop in this chapter is provided by the atmospheric-noise data shown in Fig. 1.3. It is evident that a point process model can account for the occurrence times of the pulses. However, these times alone do not reflect all of the significant features. The amplitudes of the pulses exhibit wide variation and have a strong influence on a radio receiver operating at low frequencies. Even a first-approximation model for low-frequency atmospheric noise should, therefore, include the amplitude as well as occurrence time of each pulse. It is this procedure of endowing each temporal point with an ancillary variable, an amplitude in this instance, which characterizes the models of this chapter.

Keywords

Poisson Process Occurrence Time Counting Process Independent Increment Disjoint Region 
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. 1991

Authors and Affiliations

  • Donald L. Snyder
    • 1
  • Michael I. Miller
    • 1
  1. 1.Electronic Systems and Signals Research Laboratory, Department of Electrical EngineeringWashington UniversitySt. LouisUSA

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