时间序列退化点检测的matlab代码
时间: 2023-06-15 20:03:55 浏览: 130
以下是一个简单的时间序列退化点检测的matlab代码示例:
```matlab
clc; clear; close all;
% 生成数据
x = [sin(0:0.1:2*pi), 3+sin(0.1:0.1:2*pi), 2+sin(0.05:0.1:2*pi), 4+sin(0.15:0.1:2*pi)];
x = x + 0.5*randn(size(x));
% 绘制原始数据
figure;
plot(x);
title('原始数据');
% 计算一阶差分
delta_x = diff(x);
% 计算均值和标准差
mu = mean(delta_x);
sigma = std(delta_x);
% 根据标准差的倍数来确定阈值
threshold = 3*sigma;
% 检测退化点
degradation_points = find(abs(delta_x) > threshold);
% 绘制退化点
figure;
plot(x);
hold on;
plot(degradation_points, x(degradation_points), 'rx', 'LineWidth', 2, 'MarkerSize', 10);
title('退化点检测结果');
```
该代码的思路是首先计算时间序列数据的一阶差分,然后通过均值和标准差来确定一个阈值,如果差分的绝对值大于阈值,则认为该点是一个退化点。最后将退化点标记在原始数据上。这只是一个简单的示例,实际应用中可能需要考虑更多的因素。
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