CAJ | 학술논문

神经元细胞通过动作电位进行通信，这些动作电位包含了神经元活动的最关键信息。在论述动作电位在离散小波变换(DWT)域的稀疏特性和分析压缩感知(Compressive Sensing, CS)测量动作电位的基础上，该文提出了一种采用随机滤波对动作电位进行压缩感知测量的方法。从信号恢复和物理可实现性两方面，对比了3种压缩测量的实现方法，从对实测数据的处理结果说明基于随机滤波CS的动作电位测量方案是一种能对动作电位进行压缩，系统复杂度低且最易实现的压缩采样方案。
신경원세포통과동작전위진행통신，저사동작전위포함료신경원활동적최관건신식。재논술동작전위재리산소파변환(DWT)역적희소특성화분석압축감지(Compressive Sensing, CS)측량동작전위적기출상，해문제출료일충채용수궤려파대동작전위진행압축감지측량적방법。종신호회복화물리가실현성량방면，대비료3충압축측량적실현방법，종대실측수거적처리결과설명기우수궤려파CS적동작전위측량방안시일충능대동작전위진행압축，계통복잡도저차최역실현적압축채양방안。
Neurons Action Potentials (NAP) contain the most critical information of neurons actions. Based on the discussion for the sparsity characteristics of NAP presented in the DWT domain, and the analysis of related Compressed Sensing (CS) measurements, a compressed sampling method for NAP based on random convolution is proposed. For the aspects of the signal recovery and physical realization, three compression measurement methods are compared. The experiment results show compressed sampling method for NAP based on random convolution is the best compressed sampling scheme of the three for its system realization is simplest.