Poisson Point Processes

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  • Poisson Point Processes Book Detail

  • Author : Roy L. Streit
  • Release Date : 2010-09-15
  • Publisher : Springer Science & Business Media
  • Genre : Technology & Engineering
  • Pages : 274
  • ISBN 13 : 1441969233
  • File Size : 62,62 MB

Poisson Point Processes by Roy L. Streit PDF Summary

Book Description: "Poisson Point Processes provides an overview of non-homogeneous and multidimensional Poisson point processes and their numerous applications. Readers will find constructive mathematical tools and applications ranging from emission and transmission computed tomography to multiple target tracking and distributed sensor detection, written from an engineering perspective. A valuable discussion of the basic properties of finite random sets is included. Maximum likelihood estimation techniques are discussed for several parametric forms of the intensity function, including Gaussian sums, together with their Cramer-Rao bounds. These methods are then used to investigate: -Several medical imaging techniques, including positron emission tomography (PET), single photon emission computed tomography (SPECT), and transmission tomography (CT scans) -Various multi-target and multi-sensor tracking applications, -Practical applications in areas like distributed sensing and detection, -Related finite point processes such as marked processes, hard core processes, cluster processes, and doubly stochastic processes, Perfect for researchers, engineers and graduate students working in electrical engineering and computer science, Poisson Point Processes will prove to be an extremely valuable volume for those seeking insight into the nature of these processes and their diverse applications.

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Poisson Point Processes

Poisson Point Processes

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"Poisson Point Processes provides an overview of non-homogeneous and multidimensional Poisson point processes and their numerous applications. Readers will find

Lectures on the Poisson Process

Lectures on the Poisson Process

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A modern introduction to the Poisson process, with general point processes and random measures, and applications to stochastic geometry.