Representations for multivariate reciprocal Gaussian processes

Multivariate reciprocal Gaussian processes are represented as a sum of two independent processes: a piecewise Markov process, which is also represented in terms of a Wiener-type process, and a time-dependent linear transformation of a normally distributed random vector. This result is then applied t...

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Bibliographic Details
Published in:IEEE transactions on information theory 1988-01, Vol.34 (1), p.155-157
Main Authors: Carmichael, J.-P., Masse, J.-C., Theodorescu, R.
Format: Article
Language:English
Subjects:
Applied sciences
Councils
Covariance matrix
Exact sciences and technology
Gaussian processes
Information, signal and communications theory
Markov processes
Miscellaneous
Random processes
Signal and communications theory
Telecommunications and information theory
Vectors
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Summary:Multivariate reciprocal Gaussian processes are represented as a sum of two independent processes: a piecewise Markov process, which is also represented in terms of a Wiener-type process, and a time-dependent linear transformation of a normally distributed random vector. This result is then applied to the first-passage time problem.< >
ISSN:0018-9448
1557-9654
DOI:10.1109/18.2618