...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>IEEE Signal Processing Magazine >Nonparametric Estimates of Biological Transducer Functions
【24h】

Nonparametric Estimates of Biological Transducer Functions

机译：生物传感器功能的非参数估计

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

Using bootstrap local fitting to overcome parameteric regression problems. A common task in applying signal-processing methods to biological systems is estimating a transducer function. The particular system being analyzed may range from the very small, such as a retinal photoreceptor producing a voltage response on being stimulated with a flash of light, to the large and complex, such as a human patient pressing a switch on hearing a test tone through headphones. Achieving a good estimate of the transducer function from a set of data may be an important first step in understanding the underlying biological processes as well as in helping to describe the system more generally in terms of its critical components. In some applications, the form of the transducer function is already known, and estimating it may involve the optimization of just a few parameters to achieve a fit of a model curve to the experimental data. In many other applications, however, there is no standard model. This may be because the underlying process is poorly understood or the function itself represents several simpler processes interacting with each other in a complicated way. The problem of estimating a transducer function when its form is unknown can be addressed in several ways. To help set the context of the bootstrap nonparametric approach to this problem, it is useful to review two classical parametric approaches, one based on linear regression and the other on a certain class of nonlinear functions.
机译：使用bootstrap局部拟合来克服参数回归问题。将信号处理方法应用于生物系统的常见任务是估计传感器功能。被分析的特定系统的范围可以从非常小的，例如视网膜光感受器，在受到闪光灯的刺激后产生电压响应，到庞大而复杂的系统，例如人类患者按下开关以听到测试音耳机。从一组数据中获得对换能器功能的良好估计可能是理解基础生物学过程以及帮助根据其关键组件更笼统地描述系统的重要的第一步。在一些应用中，转换器功能的形式是已知的，并且估计它可能涉及仅几个参数的优化，以实现模型曲线与实验数据的拟合。但是，在许多其他应用程序中，没有标准模型。这可能是因为对基本过程的理解不充分，或者该函数本身代表了几个更简单的过程，它们以复杂的方式相互交互。可以以多种方式解决在其形式未知时估计换能器功能的问题。为了帮助设置引导程序非参数方法针对此问题的上下文，回顾两种经典的参数方法非常有用，一种基于线性回归，另一种基于特定类别的非线性函数。

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