基于区间2型自适应神经模糊推理系统的人工心脏起搏器设计与稳定性分析

Q3 Dentistry
Asghar Dabiri, N. J. Dabanloo, F. Nooshiravan, K. Maghooli
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引用次数: 0

摘要

本文介绍了一种基于区间2型模糊系统(IT2FS)的自适应神经模糊推理系统(ANFIS)起搏器控制器的MATLAB设计和仿真。在设计了1型模糊逻辑模型后,验证了所设计系统在时域(单位阶跃响应)上的稳定性。在以前的工作中,对1型(IT1FS)模型的阶跃响应进行了分析,并与其他PID和模糊模型进行了比较,其中仅使用最小二乘估计和反向传播算法来调整隶属度函数和生成1型fis(模糊推理系统)文件,但在当前的工作中使用了显示出更好结果的模糊C均值(FCM)方法。起搏器控制器确定起搏速率并相对于参考输入信号调节患者的心率。上升时间、超调量和稳定时间都得到了显著改善。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Interval Type-2 Adaptive Neuro-Fuzzy Inference System Based, Artificial Pacemaker Design and Stability Analysis
This paper presents design and simulation of an Interval type-2 fuzzy system (IT2FS) based, Adaptive neuro-fuzzy inference system(ANFIS) pacemaker controller in MATLAB. After designing the type-1 fuzzy logic model, the stability of the designed system has been verified in the time-domain (unit step response). In previous works, type-1 (IT1FS) model step response was analyzed and compared with the other PID and Fuzzy models that only least-square-estimation and the backpropagation algorithms are used for tuning membership functions and generation of type-1 fis (fuzzy inference system) file, but at current work Fuzzy C Means (FCM) method that shows better results has been used. The pacemaker controller determines the pacing rate and adjusts the heart rate of the patient with respect to the reference input signal. The rise-time, overshoot and settling-time have been improved significantly.
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来源期刊
CiteScore
1.20
自引率
0.00%
发文量
46
期刊介绍: MEDICAL IMPLANTS are being used in every organ of the human body. Ideally, medical implants must have biomechanical properties comparable to those of autogenous tissues without any adverse effects. In each anatomic site, studies of the long-term effects of medical implants must be undertaken to determine accurately the safety and performance of the implants. Today, implant surgery has become an interdisciplinary undertaking involving a number of skilled and gifted specialists. For example, successful cochlear implants will involve audiologists, audiological physicians, speech and language therapists, otolaryngologists, nurses, neuro-otologists, teachers of the deaf, hearing therapists, cochlear implant manufacturers, and others involved with hearing-impaired and deaf individuals.
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