• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Computational Biology and Bioinformatics, IEEE/ACM Transactions on >A Hybrid EKF and Switching PSO Algorithm for Joint State and Parameter Estimation of Lateral Flow Immunoassay Models
【24h】

A Hybrid EKF and Switching PSO Algorithm for Joint State and Parameter Estimation of Lateral Flow Immunoassay Models

机译：混合EKF和切换PSO算法在横向流免疫分析模型联合状态和参数估计中的应用。

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In this paper, a hybrid extended Kalman filter (EKF) and switching particle swarm optimization (SPSO) algorithm is proposed for jointly estimating both the parameters and states of the lateral flow immunoassay model through available short time-series measurement. Our proposed method generalizes the well-known EKF algorithm by imposing physical constraints on the system states. Note that the state constraints are encountered very often in practice that give rise to considerable difficulties in system analysis and design. The main purpose of this paper is to handle the dynamic modeling problem with state constraints by combining the extended Kalman filtering and constrained optimization algorithms via the maximization probability method. More specifically, a recently developed SPSO algorithm is used to cope with the constrained optimization problem by converting it into an unconstrained optimization one through adding a penalty term to the objective function. The proposed algorithm is then employed to simultaneously identify the parameters and states of a lateral flow immunoassay model. It is shown that the proposed algorithm gives much improved performance over the traditional EKF method.
机译：本文提出了一种混合扩展卡尔曼滤波（EKF）和切换粒子群优化（SPSO）算法，通过可用的短时间序列测量来联合估计侧向免疫测定模型的参数和状态。我们提出的方法通过对系统状态施加物理约束来推广众所周知的EKF算法。注意，在实践中经常遇到状态约束，这在系统分析和设计中引起相当大的困难。本文的主要目的是通过最大化概率方法将扩展的卡尔曼滤波和约束优化算法相结合来解决具有状态约束的动态建模问题。更具体地，最近开发的SPSO算法通过将惩罚项添加到目标函数来将其转换为无约束的优化，从而解决了该约束的优化问题。然后采用提出的算法同时识别侧向免疫测定模型的参数和状态。结果表明，与传统的EKF方法相比，该算法具有更好的性能。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号