摘要
连续循环平均去卷积(Continuous Loop Averaging Deconvolution,CLAD)方法是近年来提出的高刺激率条件下提取听觉诱发电位(Auditory Evoked Potential,AEP)的有效方法.该方法对刺激序列的频域特性提出限制,给刺激序列的生成带来挑战.本文在差分进化(Differential Evolution,DE)算法的基础上,提出一种解空间收缩的差分进化(solution-space contraction DE,scDE)算法;该算法将刺激序列的频域约束和抖动量融合成一个单目标优化函数.根据抖动量的变化范围,提出新的变异算子,在维持种群多样性的同时保证搜索空间动态缩减从而生成有序性的最优刺激序列.该方法可以自动地生成各种参数下的低抖动率刺激序列,和传统随机生成序列人工筛选方式相比在保证噪声抑制能力的同时工作效率大大提高且抖动率更小.
Continuous loop averaging deconvolution （CLAD） is a newly developed method to recover the transient auditory evoked potential （AEP） from responses evoked by high stimulus rate sequences. This method brings forward a challenge in the gen- eration of an appropriate stimulus sequence which will affect the deconvolution performance. We proposed a variant of differential evolution （DE） algorithm, namely solution-space contraction differential evolution （scDE） algorithm to optimize the sequence asso- ciatexl with an objective function defined in terms of the jitter ratio （JR） and the constraint condition in frequency domain. A dynamic scaling factor F in the mutation process was formulated to guarantee the gradual reduction of the searching-space. The scDE algorithm can be efficient in generating required sequences under various conditions with lower JR. This study is thus significant in promoting the application of CLAD method in basic and clinical research.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2014年第8期1571-1576,共6页
Acta Electronica Sinica
基金
国家自然科学基金(No.61172033
No.61271154)
关键词
差分进化算法
去卷积
听觉诱发电位
differential evolution （DE） algorithm
deconvolution
auditory evoked potential （AEP）
