High Level Synthesis of Higher Order Continuous Time State Variable Filters with Minimum Sensitivity and Hardware Count

2006 ◽  
Author(s):  
S. Pandit ◽  
S. Kar ◽  
C. Mandal ◽  
A. Patra
Keyword(s):  
Continuous Time ◽  
Higher Order ◽  
High Level Synthesis ◽  
State Variable ◽  
Minimum Sensitivity ◽  
High Level ◽  
Order Continuous

The Estimation of Open Higher-Order Continuous Time Dynamic Models with Mixed Stock and Flow Data

1986 ◽  
Vol 2 (3) ◽  
pp. 350-373 ◽  
Author(s):  
A. R. Bergstrom
Keyword(s):  
Maximum Likelihood ◽  
Continuous Time ◽  
Dynamic Models ◽  
Higher Order ◽  
Maximum Likelihood Estimates ◽  
Order System ◽  
Exogenous Variables ◽  
Time Dynamic ◽  
Mixed Stock ◽  
Order Continuous

This article extends recent work on the Gaussian or quasi-maximum likelihood estimation of the parameters of a closed higher-order continuous time dynamic model by introducing exogenous variables into the model The method presented yields exact maximum likelihood estimates when the innovations are Gaussian and the exogenous variables are polynomials in time of degree not exceeding two, and it can be expected to yield very good estimates under more general conditions. It is applicable, in principle, to a system of any order with mixed stock and iow data. The precise formulas for its implementation are derived, in this article, for a second-order system in which both the endog-enous and exogenous variables are a mixture of stock and flow variables.

Sign in / Sign up

Export Citation Format

Share Document