Semi-Dirichlet Forms and Markov Processes

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<p>This&#xa0;book deals with analytic treatments of Markov processes. Symmetric Dirichlet forms and&#xa0;their associated Markov processes are important and powerful tools&#xa0;in the theory of Markov&#xa0;processes and their applications. The theory&#xa0;is well studied and used in various fields. In this monograph, we intend to&#xa0;generalize the theory to non-symmetric and time dependent semi-Dirichlet forms. By this generalization, we can cover the wide class of Markov processes and analytic theory which do not possess the dual&#xa0;Markov processes. In particular, under the semi-Dirichlet form setting, the stochastic calculus is not well established yet.&#xa0;In this monograph, we intend to give an introduction to such calculus. Furthermore, basic examples different from the symmetric cases are given.&#xa0;The&#xa0;text is written&#xa0;for graduate students, but also&#xa0;researchers.</p>