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Noise Attenuation Estimation for Maximum Length Sequences in Deconvolution Process of Auditory Evoked Potentials

机译:听觉诱发电位反卷积过程中最大长度序列的噪声衰减估计

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摘要

The use of maximum length sequence (m-sequence) has been found beneficial for recovering both linear and nonlinear components at rapid stimulation. Since m-sequence is fully characterized by a primitive polynomial of different orders, the selection of polynomial order can be problematic in practice. Usually, the m-sequence is repetitively delivered in a looped fashion. Ensemble averaging is carried out as the first step and followed by the cross-correlation analysis to deconvolve linearonlinear responses. According to the classical noise reduction property based on additive noise model, theoretical equations have been derived in measuring noise attenuation ratios (NARs) after the averaging and correlation processes in the present study. A computer simulation experiment was conducted to test the derived equations, and a nonlinear deconvolution experiment was also conducted using order 7 and 9 m-sequences to address this issue with real data. Both theoretical and experimental results show that the NAR is essentially independent of the m-sequence order and is decided by the total length of valid data, as well as stimulation rate. The present study offers a guideline for m-sequence selections, which can be used to estimate required recording time and signal-to-noise ratio in designing m-sequence experiments.
机译:已经发现使用最大长度序列(m序列)有益于在快速刺激下恢复线性和非线性分量。由于m序列完全由不同阶数的原始多项式来表征,因此在实践中多项式阶数的选择可能会出现问题。通常,m序列以循环方式重复传递。第一步是进行集合平均,然后进行互相关分析以对线性/非线性响应进行反卷积。根据基于加性噪声模型的经典降噪特性,在本研究的平均和相关过程之后,已经推导了测量噪声衰减比(NAR)的理论方程。进行了计算机仿真实验以测试导出的方程式,并且还使用阶数为7和9的m序列进行了非线性反卷积实验,以利用实际数据解决该问题。理论和实验结果均表明,NAR基本上与m序列顺序无关,并且取决于有效数据的总长度以及刺激率。本研究为m序列选择提供了指南,可用于在设计m序列实验中估计所需的记录时间和信噪比。

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