Learn the basics of white noise theory with White Noise Distribution Theory. This book covers the mathematical foundation and key applications of white noise theory without requiring advanced knowledge in this area. This instructive text specifically focuses on relevant application topics such as integral kernel operators, Fourier transforms, Laplacian operators, white noise integration, Feynman integrals, and positive generalized functions. Extremely well-written by one of the field's leading researchers, White Noise Distribution Theory is destined to become the definitive introductory resource on this challenging topic.

chapter 1|5 pages

Introduction to White Noise

chapter 2|7 pages


chapter 5|14 pages

The S-Transform

chapter 7|16 pages

Delta Functions

chapter 8|25 pages

Characterization Theorems

chapter 9|18 pages

Differential Operators

chapter 10|26 pages

Integral Kernel Operators

chapter 11|42 pages

Fourier Transforms

chapter 12|50 pages

Laplacian Operators

chapter 13|66 pages

White Noise Integration

chapter 14|12 pages

Feynman Integrals

chapter 15|18 pages

Positive Generalized Functions