Talk:Christiaan Heij

Notability tag
A notability tag has been added to the article, with the following comment, see here:
 * Tag for notability. Still an assistant professor with an h-index of 12, for someone out this long, makes me suspicious that he does not pass

At creating this article, I had similar doubts, and wondered about the same thing. I can only guess, that Heij had other priorities, but this doesn't add up either. The reason I started and did finished this article is, that Heij is first author of several books in the field, see also world cat.

I definitely think that assistant professors should not be included in Wikipedia, but there is always an exception to the rule. An h-index of 12 seems that his work has (theoretically) enough impact, regarding "(full) professors in the social sciences had average h-indices ranging from 2.8 (in law) to 7.6 (in economics)," (h-index, wikipedia). -- Mdd (talk) 08:19, 20 January 2015 (UTC)
 * I know from personal acquaintance that people in the Dutch academic system can sometimes wait a long time at what seems too-low of a rank for a position to open up (in general, unlike the US, it is less common to be promoted to a new rank in the same faculty slot) but also that because the Dutch system gives assistant professors the equivalent of tenure you can find some assistants who do not have the research productivity you would expect in the US. Heij seems on the face of it to be in the latter class to me. And an h-index should be considered in light of the person's seniority — 12, for someone with a 1980s Ph.D., is nothing special. But pure mathematics can be a low-citation field so if you have sronger evidence for the significance of his research than raw numbers that might be more informative. —David Eppstein (talk) 08:38, 20 January 2015 (UTC)


 * There seem to be (some) significant coverage of Heij's work, looking at one publication for a start. It for example learns us, that
 * Ivan Markovsky (of the University of Brussels) more often cites his work;
 * Roorda (of the University of Twente) and Heij are credited for presenting a new total least squares algorithms, specifically for system identification, and
 * Roorda and Heij is credited extending "The behavioral approach to system theory put forward by Willems (1986, 1987)..."
 * Now this is just a start. I fully agree, that incorporating this kind of info into the article might be more informative. -- Mdd (talk) 09:31, 20 January 2015 (UTC)

Quotes on Roorda and C. Heij (2007), an example

 * Since the publication of the singular value decomposition based total least squares algorithm [27], many new total least squares algorithms have been developed and, as a result, the number of applications in total least squares and errors-in-variables modeling has increased in the last decade. Total least squares is applied in computer vision [58], image reconstruction [65, 54, 22], speech and audio processing [39, 29], modal and spectral analysis [89, 93], linear system theory [14, 13], system identification [66, ....
 * [66] B. Roorda and C. Heij. Global total least squares modeling of multivariate time series. IEEE Trans. Automat. Control, 40(1):50–63, 1995.
 * Markovsky, Ivan, and Sabine Van Huffel. "Overview of total least-squares methods." Signal processing 87.10 (2007): 2283-2302.


 * The approach of Roorda and Heij [14], [16] is based on solving the inner minimization problem, the misfit computation, by using isometric state representation and subsequently used alternating least squares or Gauss–Newton type algorithm for the outer minimization problem. They use a state space representation with driving input. Our approach of solving the GTLS problem, is different. We relate the identification problem to the STLS problem (1) and subsequently use solution methods developed for the STLS problem. Also we use a kernel representation of the system.
 * Markovsky, Ivan, et al. "Application of structured total least squares for system identification and model reduction." Automatic Control, IEEE Transactions on 50.10 (2005): 1490-1500.


 * The behavioral approach to system theory put forward by Willems (1986, 1987) is a manifestation of the representation free thinking. Deriving dynamic models from data, i.e., system identification, has been considered in the behavioral setting in Roorda and Heij (1995), Roorda (1995), and Markovsky, Willems, Van Huffel, De Moor, and Pintelon (2005).
 * Markovsky, Ivan. "Structured low-rank approximation and its applications." Automatica 44.4 (2008): 891-909.


 * Optimal EIV filtering can be approached also in a deterministic context, as an optimization problem along the line followed by Roorda and Heij [9], as described in [6]. An approach of this kind has been recently used also in [10].
 * Diversi, Roberto, Roberto Guidorzi, and Umberto Soverini. "Kalman filtering in extended noise environments." Automatic Control, IEEE Transactions on 50.9 (2005): 1396-1402.


 * The Kalman filter cannot be directly applied to such EIV processes as discussed in [26], [28]. Nevertheless, an extension of the Kalman filter, where the state and the output are optimally estimated in the presence of state and output noise is proposed in [29].
 * [28] B. Roorda and C. Heij, “Global total least squares modeling of multivariable time series,” IEEE Transactions on Automatic Control, vol. 40, no. 1, pp. 50–63, Jan. 1995.
 * Lundquist, Christian, Umut Orguner, and Fredrik Gustafsson. "Extended target tracking using polynomials with applications to road-map estimation." Signal Processing, IEEE Transactions on 59.1 (2011): 15-26.

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