Title :
Efficient computation of gradient and hessian of likelihood function in linear dynamic systems
Author :
Gupta, Narendra K.
Author_Institution :
Systems Control, Incorporated, Palo Alto, CA, USA
fDate :
10/1/1976 12:00:00 AM
Abstract :
This technical note describes a computationally efficient procedure to determine the first and second gradients of the likelihood function for parameter estimation in linear dynamic systems. The results presented here are extensions, of the sensitivity functions reduction procedure of [1]. An operation count shows the value of the new algorithm.
Keywords :
Linear systems, stochastic continuous-time; Parameter estimation; maximum-likelihood (ML) estimation; Automatic control; Autoregressive processes; Control systems; Difference equations; H infinity control; Least squares methods; Linear systems; Maximum likelihood estimation; Parameter estimation; Stochastic processes;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.1976.1101359
