Title :
On Powers of Gaussian White Noise
Author :
Balakrishnan, A.V. ; Mazumdar, Ravi R.
Author_Institution :
Depts. of Electr. Eng. & Math., Univ. of California, Los Angeles, CA, USA
Abstract :
Classical Gaussian white noise in communications and signal processing is viewed as the limit of zero-mean second-order Gaussian processes with a compactly supported flat spectral density as the support goes to infinity. The difficulty of developing a theory to deal with nonlinear transformations of white noise has been to interpret the corresponding limits. In this paper, we show that a renormalization and centering of powers of band-limited Gaussian processes is Gaussian white noise, and, as a consequence, homogeneous polynomials under suitable renormalization remain white noises.
Keywords :
Gaussian noise; Gaussian processes; polynomials; white noise; Gaussian white noise; band-limited Gaussian process; flat spectral density; homogeneous polynomials; nonlinear transformations; signal processing; zero-mean second-order Gaussian process; Additives; Gaussian processes; Hilbert space; Noise measurement; Random variables; White noise; Asymptotics; Gaussian white noise; band-limited processes; finitely additive measures; weak distributions;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.2011.2158062