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.