Department of Biostatistics and Anesthesiology, Columbia University Medical Center, PH5-505, New York, NY 10032, USA.
Math Biosci. 2010 Mar;224(1):10-23. doi: 10.1016/j.mbs.2009.11.010. Epub 2009 Dec 1.
System Identification refers to the problem of identifying a model or description of a system based on a stretch of input and the corresponding output from the system. The paired-pulse paradigm or the conditioning test pulse paradigm is often used in neurophysiology experiments. In this work we provide a statistical framework for the conditioning test pulse paradigm which also serves as a system identification tool for quadratic or second order Volterra systems. A nonparametric spectral domain based methodology is proposed for the quadratic system identification. It is shown that by carrying out the analysis in the spectral domain one needs to perform only a single set of double pulse experiments as opposed to multiple sets of experiments in the time domain. Simulation studies are performed to assess the performance of the methodology and to study the conditions under which the methods are expected to perform well.
系统辨识是指根据系统的输入和相应的输出，确定系统模型或描述的问题。在神经生理学实验中，通常使用双脉冲范式或条件测试脉冲范式。在这项工作中，我们为条件测试脉冲范式提供了一个统计框架，该框架也可作为二次或二阶 Volterra 系统的系统识别工具。提出了一种基于非参数谱域的二次系统辨识方法。结果表明，通过在谱域中进行分析，与在时域中进行多组实验相比，只需要进行一组双脉冲实验。进行了模拟研究，以评估该方法的性能，并研究该方法有望表现良好的条件。
