Stochastic Differential Equations

'Et moi, ..~ si lavait su CO.llUlJalt en revc:nir, One acMcc matbcmatica bu JaIdcred the human rac:c. It bu put COIDIDOD beet je n'y serais point aBe.' Jules Verne wbac it bdoup, 0Jl !be~ IbcII t to !be dusty cauialcr Iabc&d 'diMardod The series is divergent; thc:reforc we may be -'. I!.ticT. Bc:I1 able to do something with it. O. Hcavisidc Mathematics is a tool for thought. A highly necessary tool in a world when: both feedback and non linearities abound. Similarly. all kinds of parts of mathematics serve as tools for other parts and for other sciences. Applying a simple rewriting rule to the quote on the right above one finds such statcmalts as: 'One service topology has rendered mathematical physics ... ; 'One service logic has rendered c0m puter science ...'; 'One service category theory has rendered mathematics ...'. All arguably true. And all statements obtainable this way form part of the raison d'etre of this series. This series, Mathematics and Its Applications. started in 19n. Now that over one hundred volumes have appeared it seems opportune to reexamine its scope. At the time I wrote "Growing specialization and diversification have brought a host of monographs and textbooks on increasingly specialized topics. However. the 'tree' of knowledge of mathematics and related fields does not grow only by putting forth new branc:hes. It also happens, quite often in fact, that branches which were thought to be completely.

Contenu
Introduction: Origin of Stochastic Differential Equations.- I. Stochastic Processes Short ResumÉ.- 1. Introductory Remarks.- 2. Probability and Random Variables.- 3. Stochastic Processes Basic Concepts.- 4. Gaussian Processes.- 5. Stationary Processes.- 6. Markov Processes.- 7. Processes With Independent Increments; Wiener Process And Poisson Process.- 8. Point Stochastic Processes.- 9. Martingales.- 10. Generalized Stochastic Processes; White Noise.- 11. Processes with Values in Hilbert Space.- 12. Stochastic Operators.- Examples.- II. Stochastic Calculus: Principles and Results.- 13. Introductory Remarks.- 14. Processes of Second Order; Mean Square Analysis.- 15. Analytical Properties of Sample Functions.- 16. ITÔ Stochastic Integral.- 17. Stochastic Differentials. ITÔ Formula.- 18. Counting Stochastic Integral.- 19. Generalizations.- Examples.- III. Stochastic Differential Equations: Basic Theory.- 20. Introductory Remarks.- 21. Regular Stochastic Differential Equations.- 22. ITÔ Stochastic Differential Equations.- 23. Stochastic Abstract Differential Equations.- IV. Stochastic Differential Equations: Analytical Methods.- 24. Introductory Remarks.- 25. Systems with Random Initial Conditions.- 26. Linear Systems with Random Excitation.- 27. Nonlinear Systems with Random Excitation.- 28. Stochastic Systems.- 29. Stochastic Partial Differential Equations.- V. Stochastic Differential Equations: Numerical Methods.- 30. Introductory Remarks.- 31. Deterministic Equations: Basic Numerical Methods.- 32. Approximate Schemes for Regular Stochastic Equations.- 33. Numerical Integration of ITÔ Stochastic Equations.- VI. Applications: Stochastic Dynamics of Engineering Systems.- 34. Introduction.- 35. Random Vibrations of Road Vehicles.- 36. Response of Structures toTurbulent Field.- 37. Response of Structures To Earthquake Excitation.- 38. Response of Structures to Sea Waves.- 39. Stochastic Stability of Structures.- 40. Other Problems.- Appendix..- A.1. Cauchy formula.- A.2. Gronwall-Bellman inequality.- References.