相关性和卷积
互相关、自相关、互协方差、自协方差、线性卷积和循环卷积
Signal Processing Toolbox™ 提供了一系列相关性和卷积函数,用于检测信号相似性。确定周期性,找到隐藏在长数据记录中的感兴趣的信号,并测量信号之间的延迟以同步它们。计算线性时不变 (LTI) 系统对输入信号的响应,执行多项式乘法,并执行循环卷积。
函数
主题
常见应用
- Find a Signal in a Measurement
Determine if a signal matches a segment of a noisy longer stream of data. - Align Two Simple Signals
Learn to align signals of different lengths using cross-correlation. - 将信号与不同开始时间对齐
同步不同传感器在不同时刻采集的数据。 - 使用互相关性对齐信号
使用互相关性融合异步数据。 - 使用自相关求周期性
验证含噪信号中是否存在周期,并确定其持续时间。 - Echo Cancellation
Use autocorrelation to filter out an echo from a speech recording.
自相关和互相关
- 多通道输入的互相关
计算一个多通道信号的自相关和互相关。 - 样本自相关的置信区间
为白噪声过程的自相关序列创建置信区间。 - Autocorrelation Function of Exponential Sequence
Compute the autocorrelation of an exponential sequence and compare it to the analytic result. - Cross-Correlation of Two Exponential Sequences
Compute the cross-correlation of two exponential sequences and compare it to the analytic result. - Autocorrelation of Moving Average Process
Use filtering to introduce autocorrelation into a white noise process. - Cross-Correlation of Two Moving Average Processes
Find and plot the cross-correlation sequence between two moving average processes. - Cross-Correlation of Delayed Signal in Noise
Use the cross-correlation sequence to detect the time delay in a noise-corrupted sequence. - Cross-Correlation of Phase-Lagged Sine Wave
Use the cross-correlation sequence to estimate the phase lag between two sine waves. - 线性和循环卷积
建立线性卷积和循环卷积之间的等效关系。