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Likelihood ratios with gauss measure noise models

Stochastic Equations

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Part of the Lecture Notes in Mathematics book series (LNM,volume 695)

Abstract

We present a formula for likelihood functionals for signals in which the corrupting noise is modelled as white noise with Gauss measure rather than the usual Wiener process. The main difference is the appearance of an additional term corresponding to the conditional mean square error. By way of one application we consider the ‘order-disorder’ problem of Shiryayev.

Keywords

  • Stochastic Differential Equation
  • Cauchy Sequence
  • Gauss Measure
  • Additive Probability Measure
  • Weak Distribution

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References

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© 1978 Springer-Verlag

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Balakrishnan, A.V. (1978). Likelihood ratios with gauss measure noise models. In: Kallianpur, G., Kölzow, D. (eds) Measure Theory Applications to Stochastic Analysis. Lecture Notes in Mathematics, vol 695. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0062657

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  • DOI: https://doi.org/10.1007/BFb0062657

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-09098-4

  • Online ISBN: 978-3-540-35556-4

  • eBook Packages: Springer Book Archive