Title :
Shaping filter representation of nonstationary colored noise
Author :
Brandenburg, L.H. ; Meadows, H.E.
fDate :
1/1/1971 12:00:00 AM
Abstract :
The problem of determining a shaping filter for nonstationary colored noise is considered. The shaping filter transforms white noise into a possibly nonstationary random process (having no white noise component) with a specified covariance function. A set of conditions to be satisfied by the covariance function leads to the determination of a shaping filter. The shaping filter coefficients are simply related to the solution of a matrix Riccati equation. In order to formulate the Riccati equation, basic results concerning the mean-square differentiability of a random process are developed. If the Riccati equation can not be defined, an autonomous (zero-input) shaping filter may be easily determined.
Keywords :
Covariance factorization; Noise; Nonstationary stochastic processes; Shaping filters; Colored noise; Covariance matrix; Differential equations; Kalman filters; Maximum likelihood detection; Noise shaping; Nonlinear filters; Random processes; Riccati equations; White noise;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.1971.1054585