Abstract:
:We present a procedure that optimally adjusts specified parameters of a mathematical model to describe a set of measured data. The technique integrates a dynamic systems-simulation language with a robust algorithm for nonlinear parameter estimation, and it can be implemented on a microcomputer. Sensitivity functions are generated that indicate how the operation of the model is affected by each updated parameter. This procedure offers a greater resolution of optimal parameter values than other, less rigorous methods. To illustrate this technique we have applied it to the model of human smooth pursuit eye movements proposed by D.A. Robinson and colleagues (1986).
journal_name
Biol Cybernjournal_title
Biological cyberneticsauthors
Huebner WP,Saidel GM,Leigh RJdoi
10.1007/BF00201441subject
Has Abstractpub_date
1990-01-01 00:00:00pages
265-73issue
4eissn
0340-1200issn
1432-0770journal_volume
62pub_type
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