Conditionally Linear and Non-Gaussian Processes

  • R. R. Mohler
  • W. J. Kolodziej


A new theory and corresponding methodology is evolving for certain classes of nonlinear non-Gaussian signal processing. This research considers particular statistical model structures such as conditionally linear or bilinear. Some non-Gaussian distributions, which arise in underwater acoustical signal processing, are included, as are others. The results are based on rigorous developments related to, but not limited to, bilinear and conditionally Gaussian processes. Parameter or state estimation (e.g., acoustic source location) are studied as well as preliminary results in information transmission and coding.


Gaussian Process Stochastic Differential Equation Wiener Process Linear Code Optimal Code 
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. 1989

Authors and Affiliations

  • R. R. Mohler
    • 1
    • 2
  • W. J. Kolodziej
    • 1
  1. 1.Department of Electrical and Computer EngineeringOregon State UniversityCorvallisUSA
  2. 2.Naval Postgraduate SchoolMontereyUSA

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