It takes the average reader 7 hours and 16 minutes to read Large Deviations for Stochastic Processes by Jin Feng
Assuming a reading speed of 250 words per minute. Learn more
The book is devoted to the results on large deviations for a class of stochastic processes. Following an introduction and overview, the material is presented in three parts. Part 1 gives necessary and sufficient conditions for exponential tightness that are analogous to conditions for tightness in the theory of weak convergence. Part 2 focuses on Markov processes in metric spaces. For a sequence of such processes, convergence of Fleming's logarithmically transformed nonlinear semigroups is shown to imply the large deviation principle in a manner analogous to the use of convergence of linear semigroups in weak convergence. Viscosity solution methods provide applicable conditions for the necessary convergence. Part 3 discusses methods for verifying the comparison principle for viscosity solutions and applies the general theory to obtain a variety of new and known results on large deviations for Markov processes. In examples concerning infinite dimensional state spaces, new comparison principles are derived for a class of Hamilton-Jacobi equations in Hilbert spaces and in spaces of probability measures.
Large Deviations for Stochastic Processes by Jin Feng is 426 pages long, and a total of 109,056 words.
This makes it 144% the length of the average book. It also has 133% more words than the average book.
The average oral reading speed is 183 words per minute. This means it takes 9 hours and 55 minutes to read Large Deviations for Stochastic Processes aloud.
Large Deviations for Stochastic Processes is suitable for students ages 12 and up.
Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.
When deciding what to show young students always use your best judgement and consult a professional.
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