Bankman I N, Thakor N V
Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD 21205.
Med Biol Eng Comput. 1990 Nov;28(6):544-9. doi: 10.1007/BF02442605.
A weighted filter for noise reduction in nonrecurrent step signals where adaptive filtering cannot be applied is described. An optimal correction of a conventional finite impulse response (FIR) filter is achieved by using a priori knowledge of noise variance and a continuous estimation of the error signal's power. The weighted filter provides an optimal compromise between noise filtering and distortionless tracking. The prior knowledge required is that of the noise power and the lowest frequency in the noise spectrum. Application of the weighted filter to the saccadic electro-oculogram (EOG) results in better estimations of saccade duration and velocity.
本文描述了一种用于非递归阶跃信号降噪的加权滤波器，该信号无法应用自适应滤波。通过使用噪声方差的先验知识和误差信号功率的连续估计，实现了对传统有限脉冲响应（FIR）滤波器的最优校正。加权滤波器在噪声滤波和无失真跟踪之间提供了最优折衷。所需的先验知识是噪声功率和噪声频谱中的最低频率。将加权滤波器应用于眼跳电图（EOG）可更好地估计眼跳持续时间和速度。
