请教特征提取的一些函数,有些地方不太明白

import numpy as np # 均方根 def featureRMS(data): return np.sqrt(np.mean(data ** 2, axis=0)) # 取绝对值求各列均值 def featureMAV(data): return np.mean(np.abs(data), axis=0) # 求离散的差值，按列的后尾元素向上面的元素进行求差，然后取绝对值再求所有矩阵同一元素位置的和，最后除以矩阵个数 def featureWL(data): return np.sum(np.abs(np.diff(data, axis=0)), axis=0) / data.shape[0] # def featureZC(data, threshold=10e-7): numOfZC = [] channel = data.shape[1] length = data.shape[0] for i in range(channel): count = 0 for j in range(1, length): diff = data[j, i] - data[j - 1, i] mult = data[j, i] * data[j - 1, i] if np.abs(diff) > threshold and mult < 0: count = count + 1 numOfZC.append(count / length) return np.array(numOfZC) def featureSSC(data, threshold=10e-7): numOfSSC = [] channel = data.shape[1] length = data.shape[0] for i in range(channel): count = 0 for j in range(2, length): diff1 = data[j, i] - data[j - 1, i] diff2 = data[j - 1, i] - data[j - 2, i] sign = diff1 * diff2 if sign > 0: if (np.abs(diff1) > threshold or np.abs(diff2) > threshold): count = count + 1 numOfSSC.append(count / length) return np.array(numOfSSC) 

能请教一下 MAV 、WL 、ZC 、SSC4 个函数的都是啥数学公式？ 网上搜的那些都搜不到

大学数学早就还给老师了.....