教程

• 可视化小波，小波包和小波过滤器
  

  获取与特定小波家族相对应的过滤器，小波或小波包。

• Time-Frequency Analysis and Continuous Wavelet Transform
  

  了解CWT如何帮助您获得尖锐的时频表示。

• Discrete Wavelet Analysis
  

  使用离散小波变换技术分析和DENOIS信号和图像。

• Critically Sampled Wavelet Packet Analysis
  

  获得1-D信号和2-D图像的小波数据包变换。

• 匹配的追求
  

  Create sensing dictionaries and perform matching pursuit on 1-D signals.

• Lifting
  

  在执行离散小波变换的同时，使用升压来设计小波过滤器。

关于小波

• 什么是小波？
  

  了解有关小波以及如何检测信号不连续性的一般信息。

• 连续和离散的小波变换
  

  决定是使用离散或连续小波变换。

• Choose a Wavelet
  

  Learn criteria for choosing the right wavelet for your application.

Featured Examples

连续小波分析的实用介绍

执行和解释连续的小波分析。该示例可以帮助您回答常见问题，例如：连续和离散小波分析之间有什么区别？为什么频率或连续小波分析中的尺度对数间隔？在哪种类型的信号分析中，问题是连续的小波技术特别有用？

Open Live Script

Practical Introduction to Multiresolution Analysis

执行和解释基本信号多解析分析（MRA）。该示例使用模拟和真实数据来回答以下问题：多分析分析是什么意思？关于我的信号有什么见解，我可以获得多解析分析？不同MRA技术的优势和缺点是什么？这里提供的许多分析可以使用信号多解决分析仪应用程序复制。

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调制信号的连续小波分析

使用连续小波变换（CWT）分析调制信号。

Open Live Script

Denoise a Signal with the Wavelet Signal Denoiser

Use the Wavelet Signal Denoiser app to denoise a real-valued 1-D signal. You can create and compare multiple versions of a denoised signal with the app and export the desired denoised signal to your MATLAB® workspace. To reproduce the denoised signal in your workspace, or to apply the same denoising parameters to other data, you can generate and edit a MATLAB script. This example illustrates one possible workflow.

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使用小波分析和深度学习对时间序列进行分类

Classify heartbeat electrocardiogram data using deep learning and the continuous wavelet transform.

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音乐流派分类使用小波时间散射

使用小波时间散射和音频数据存储对音乐摘录进行分类。

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比例定位的波动率和相关性

有许多不同的变化wavelet transform. This example focuses on the maximal overlap discrete wavelet transform (MODWT). The MODWT is an undecimated wavelet transform over dyadic (powers of two) scales, which is frequently used with financial data. One nice feature of the MODWT for time series analysis is that it partitions the data variance by scale. To illustrate this, consider the quarterly chain-weighted U.S. real GDP data for 1974Q1 to 2012Q4. The data were transformed by first taking the natural logarithm and then calculating the year-over-year difference. Obtain the MODWT of the real GDP data down to level six with the 'db2' wavelet. Examine the variance of the data and compare that to the variances by scale obtained with the MODWT.

Open Script

Videos

Understanding Wavelets, Part 1: What Are Wavelets
Explore the fundamental concepts of wavelet transforms in this introductory MATLAB Tech Talk. This video covers what wavelets are and how you can use them to explore your data in MATLAB. The video focuses on two important wavelet transform concepts: scaling and shifting. The concepts can be applied to 2-D data such as images.

了解小波，第2部分：小波的类型变换
Explore the workings of wavelet transforms in detail. You will learn more about the continuous wavelet transforms and the discrete wavelet transform. You will also learn important applications of using wavelet transforms with MATLAB.

了解小波，第3部分：离散小波变换的示例应用
在此MATLAB技术演讲中保留其尖锐的功能的同时，了解如何使用小波来降低信号。该视频概述了使用MATLAB使用离散小波变换来降低信号的步骤。了解这种脱氧技术与其他脱氧技术的比较。

了解小波，第4部分：连续小波变换的示例应用
Explore a practical application of using continuous wavelet transforms in this MATLAB Tech Talk. Get an overview of how to use MATLAB to obtain a sharper time-frequency analysis of a signal with the continuous wavelet transform. This video uses an example seismic signal to highlight the frequency localization capabilities of the continuous wavelet transform.

Understanding Wavelets, Part 5: Machine Learning and Deep Learning with Wavelet Scattering
小波散射网络可帮助您自动从信号和图像中获取用于机器学习和深度学习应用程序的低变差功能。在此MATLAB技术演讲中，了解小波散射变换以及如何用作自动稳健功能提取器进行分类。