White noise analysis

In probability theory, a branch of mathematics, white noise analysis, otherwise known as Hida calculus, is a framework for infinite-dimensional and stochastic calculus, based on the Gaussian white noise probability space, to be compared with Malliavin calculus based on the Wiener process.[1] It was initiated by Takeyuki Hida in his 1975 Carleton Mathematical Lecture Notes.[2]

The term white noise was first used for signals with a flat spectrum.

  1. ^ Huang, Zhi-yuan; Yan, Jia-An (2000). Introduction to Infinite-Dimensional Stochastic Analysis. Dordrecht: Springer Netherlands. ISBN 9789401141086. OCLC 851373497.
  2. ^ Hida, Takeyuki (1976). "Analysis of Brownian functionals". Stochastic Systems: Modeling, Identification and Optimization, I. Mathematical Programming Studies. Vol. 5. Springer, Berlin, Heidelberg. pp. 53–59. doi:10.1007/bfb0120763. ISBN 978-3-642-00783-5.