**Lectures on Stochastic Flows and Applications**

by H. Kunita

**Publisher**: Tata Institute Of Fundamental Research 1986**ISBN/ASIN**: 3540177752**ISBN-13**: 9783540177753**Number of pages**: 130

**Description**:

The author presents basic properties of stochastic flows, specially of Brownian flows. Their relations with local characteristics and with stochastic differential equations are central problems. In the second part, as an application of the first part, various limit theorems for stochastic flows are presented.

Download or read it online for free here:

**Download link**

(620KB, PDF)

## Similar books

**Synchronization and Linearity: An Algebra for Discrete Event Systems**

by

**F. Baccelli, G. Cohen, G. J. Olsder, J. Quadrat**-

**John Wiley & Sons**

Presents new modelling and analysis techniques for the description of discrete event dynamic systems. Created within the text is a calculus which allows the derivation of analytical tools for computing the time behavior of this type of system.

(

**8162**views)

**Stochastic Analysis - Notes**

by

**I. F. Wilde**

A gentle introduction to the mathematics of Stochastic Analysis. From the table of contents: Introduction; Conditional expectation; Martingales; Stochastic integration - informally; Wiener process; Ito's formula; Bibliography.

(

**10386**views)

**Stochastic Differential Equations: Models and Numerics**

by

**Anders Szepessy, et al.**-

**KTH**

The goal of this course is to give useful understanding for solving problems formulated by stochastic differential equations models in science, engineering and finance. Typically, these problems require numerical methods to obtain a solution.

(

**3334**views)

**Lectures on Topics in Stochastic Differential Equations**

by

**Daniel W. Stroock**-

**Tata Institute of Fundamental Research**

The author's purpose in these lectures was to provide some insight into the properties of solutions to stochastic differential equations. In order to read these notes, one need only know the basic Ito theory of stochastic integrals.

(

**5387**views)