Estimating the Membrane Properties of Vestibular Type II Hair Cells using Continuous-time System Identification

被引：3
|
作者：
Pan, Siqi [1 ]
Welsh, James S. [1 ]
Brichta, Alan M. [2 ]
Drury, Hannah R. [2 ]
Stoddard, Jeremy G. [1 ]
机构：
[1] Univ Newcastle, Sch Elect Engn & Comp, Callaghan, NSW, Australia
[2] Univ Newcastle, Sch Biomed Sci & Pharm, Callaghan, NSW, Australia
来源：
IFAC PAPERSONLINE | 2020年 / 53卷 / 02期
关键词：
System identification; Continuous-time systems; Instrumental variable method; Biological systems; PATCH-CLAMP TECHNIQUES;
D O I：
10.1016/j.ifacol.2020.12.477
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper we apply a continuous-time system identification method, known as the Simplified Refined Instrumental Variable method for Continuous-time systems (SRIVC), to the problem of estimating membrane properties of vestibular Type II hair cells. Due to the non-ideal characteristics of the experimental system, additional parameters, other than those of the membrane are required to be estimated. The SRIVC algorithm is modified to allow known poles and zeros to be forced into the estimator. This modified algorithm is then applied to the identification of the membrane properties of vestibular Type II hair cells, yielding results commensurate with typically accepted values. Copyright (C) 2020 The Authors.
引用
收藏
页码：548 / 553
页数：6
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