Numerical deconvolution using system identification methods. Academic Article

abstract

• A deconvolution method is presented for use in pharmacokinetic applications involving continuous models and small samples of discrete observations. The method is based on the continuous-time counterpart of discrete-time least squares system identification, well established in control engineering. The same technique, requiring only the solution of a linear regression problem, is used both in system identification and input identification steps. The deconvolution requires no a priori information, since the proposed procedure performs system identification (including optimal selection of model order), selects the form of the input function and calculates its parametric representation and its values at specified time points.

authors

• Valko, Peter

published proceedings

• J Pharmacokinet Biopharm

author list (cited authors)

• Vajda, S., Godfrey, K. R., & Valko, P.

citation count

• 26

complete list of authors

• Vajda, S||Godfrey, KR||Valko, P

publication date

• February 1988

publisher

• Springer Nature  Publisher

published in

• Journal of Pharmacokinetics and Pharmacodynamics  Journal

keywords

• Models, Biological
• Pharmacokinetics

Digital Object Identifier (DOI)

• 10.1007/BF01061863

start page

• 85

end page

• 107

volume

• 16

issue

• 1

URL

• http%3A%2F%2Fdx.doi.org%2F10.1007%2Fbf01061863