Nonlinear parameter estimation applied to a model of smooth pursuit eye movements.

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 Cybern

journal_title

Biological cybernetics

authors

Huebner WP,Saidel GM,Leigh RJ

doi

10.1007/BF00201441

subject

Has Abstract

pub_date

1990-01-01 00:00:00

pages

265-73

issue

4

eissn

0340-1200

issn

1432-0770

journal_volume

62

pub_type

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