Title :
Calculation of the spectral density from the noise convolution integral covariance matrix
Author_Institution :
Johns Hopkins University, Laurel, MD, USA
fDate :
8/1/1981 12:00:00 AM
Abstract :
A problem which arises in system identification of continuous systems with nonuniform sampling is that of calculating the spectral density of a vector white noise process from a noise convolution integral covariance matrix. A numerical solution to this problem is presented which converges in one step.
Keywords :
Covariance matrices; Discrete-time systems; System identification; Continuous time systems; Convergence; Convolution; Covariance matrix; Iterative algorithms; Iterative methods; Parameter estimation; Symmetric matrices; System identification; White noise;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.1981.1102754
