滤波去噪

%移动平均滤波
clear
clc
close all

N_window = 5;%窗口长度(最好为奇数）
t = 0:0.1:10;
A = cos(2*pi*0.5*t)+0.3*rand(size(t));
B1 = movmean(A,N_window);
figure(1)
plot(t,A,t,B1)

%移动平均滤波
clear
clc
load('类型3_70.mat');
N_window = 5;%窗口长度(最好为奇数）
B1 = movmean(BBl_3_70,N_window);
B2 = movmedian(BBl_3_70,7);%中值滤波
plot(B2,'g');
hold on;
plot(BBl_3_70,'b');
hold on;
plot(B1,'r')

function [X2] = F_smooth(X1)
% 简单的滤波处理，主要目的在于消除毛刺和去除趋势项，寻找最大和最小值。
m = 3;   %循环的次数
N = length(X1);   %数据的长度
a = X1;
for M = 1:m
    b(1) = (3 * a(1) + 2 * a(2) + a(3) - a(4)) / 5;
    b(2) = (4 * a(1) + 3 * a(2) + 2 * a(3) + a(4)) / 10;
    for j = 3:N-2
        b(j) = (a(j-2) + a(j-1) + a(j) + a(j+1) + a(j+2)) / 5;
    end
    b(N-1) = (a(N-3) + 2 * a(N-2) + 3 * a(N-1) + 4 * a(N)) / 10;
    b(N) = (-a(N-3) + a(N-2) + 2 * a(N-1) + 3 * a(N)) / 5;
    a = b;
end
X2=a;
end