Recursive identification

L. Ljung, T. Sbderstrbm, Theory and Practice of Recursive Identification, MIT Press, Cambridge, MA, 1983... 

Crowe, C.M., Recursive Identification of Gross Errors in Linear Data Reconciliation, AJChE Journal, 34(4), 1988,541-550. (Global chi square test, measurement test)... 

Soderstrom, T., Ljung, L, and Gustavsson, I. (1978) "A theoretical analysis of recursive identification methods, Automatica, 14, 231-244. 

Given a set of experimental data, we look for the time profile of A (t) and b(t) parameters in (C.l). To perform this key operation in the procedure, it is necessary to estimate the model on-line at the same time as the input-output data are received [600]. Identification techniques that comply with this context are called recursive identification methods, since the measured input-output data are processed recursively (sequentially) as they become available. Other commonly used terms for such techniques are on-line or real-time identification, or sequential parameter estimation [352]. Using these techniques, it may be possible to investigate time variations in the process in a real-time context. However, tools for recursive estimation are available for discrete-time models. If the input r (t) is piecewise constant over time intervals (this condition is fulfilled in our context), then the conversion of (C.l) to a discrete-time model is possible without any approximation or additional hypothesis. Most common discrete-time models are difference equation descriptions, such as the Auto-.Regression with eXtra inputs (ARX) model. The basic relationship is the linear difference equation ... 

Crowe, C.M. (1988), Recursive identification of gross errors in linear data reconciliation, AIChE J. 34, 541-550... 

The appendix shows an example of a recursive procedure to calculate the pigment to binder ratio for a non-reactive coating formulation. We assume that a raw material data base contains raw material code, density, cost per unit weight, solids volume fraction, and pigment solids volume fraction. Formulas are stored in files that contain the identification and amount of... 

A Recursive Scheme for Gross Error Identification and Estimation 125... 

Figure 1 illustrates, schematically, the use of this recursive scheme for con-straints/measurements processing in any identification procedure. 

A RECURSIVE SCHEME FOR GROSS ERROR IDENTIFICATION AND ESTIMATION... 

Closed-loop identification has been addressed extensively in a linear stochastic control setting (Astrom and Wittenmark, 1989). Good discussions of early results from a stochastic control viewpoint are presented by Box (1976) and Gustavsson et al (1977). Landau and Karimi (1997) provide an evaluation of recursive algorithms for closed-loop identification. Van den Hof and Schrama (1994), Gevers (1993), and Bayard and Mettler (1992) review research on new criteria for closed-loop identification of state space or input-output models for control purposes. 

Landau, I.D., and Karimi, A., Recursive algorithms for identification in closed loop A unified approach and evaluation, Automatica 33, 8, 1499-1523 (1997). 

For the identification of the optimal sequence of hidden metastable states we can use the well-known Viterbi algorithm [30], which exploits dynamic programming techniques to resolve in a recursive manner the optimization problem... 

What is the good of this set of results The key point is the identification of a recursive strategy for obtaining the partition function. In particular, in the present setting, we note that in the high-temperature limit, Z = 2 resulting in the... 

Zhu, F. and Agrafiotis, D.K (2007) Recursive distance partitioning algorithm for common pharmacophore identification. Journal of Chemical Information and Modeling, 47,1619-1625. 

Lipkovich 1, Dmitrienko A, Denne J, Enas G. Subgroup identification based on differential effect search A recursive partitioning method for establishing response to treatment in patient subpopulations. Statistics in Medicine, 30 2601-2621, 2011. 

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