改进DE算法优化高刺激率AEP的刺激序列

Stimulus-Sequences Optimization for High-Rate AEPs Using Modified Differential Evolution Algorithm

刺激序列的性质直接影响高刺激率听觉诱发电位(Auditory evoked potentials,AEP)去卷积的性能,自动生成满足需求的刺激序列可以为高刺激率AEP的基础和应用研究带来极大便利。以刺激序列的抖动量为优化变量利用差分进化(Differential evolution,DE)算法定义了约束条件下的目标函数。根据抖动量的变化范围,改进了DE搜索的变异算子实现搜索空间动态缩减。该方法可以方便地生成各种参数(包括刺激率、频带范围、扫程长度和采样频率)的低抖动率刺激序列。通过实测脑电信号合成的数据检验,本方法得到的各种刺激序列都取得了较好的效果。

The generation of appropriate stimulus sequences in an automatic way can facilitate the research and application in the study of auditory evoked-potentials （AEPs） under high stimulus rate paradigm.This paper proposes an applicable method to generate the optimized sequences using a modified differential evolution （DE） algorithm.This method defines an objective function in terms of jitter ratio （JR） and underlying constraint condition derived from the spectrum of the sequence.The performance of the algorithm is improved by gradually reducing the searching-space guaranteed by a dynamic scaling factor in the mutation process.Four compatible sequences are given to compare with the manual selected sequences as reported.The synthetic data are used to justify the feasibility of the proposed method,which presents a less jitter ratio of the underlying sequence.