1st Edition
Stochastic Analysis for Gaussian Random Processes and Fields With Applications
Covariances and Associated Reproducing Kernel Hilbert Spaces. Gaussian Random Fields. Stochastic Integration for Gaussian Random Fields. Skorokhod and Malliavin Derivatives for Gaussian Random Fields. Filtering with General Gaussian Noise. Equivalence and Singularity. Markov Property of Gaussian Fields. Markov Property of Gaussian Fields and Dirichlet Forms. Bibliography. Index.
Biography
Vidyadhar Mandrekar is a professor in the Department of Statistics and Probability at Michigan State University. He earned a PhD in statistics from Michigan State University. His research interests include stochastic partial differential equations, stationary and Markov fields, stochastic stability, and signal analysis.
Leszek Gawarecki is head of the Department of Mathematics at Kettering University. He earned a PhD in statistics from Michigan State University. His research interests include stochastic analysis and stochastic ordinary and partial differential equations.
