分类

对信号属性进行分类，通过“序列到序列”分类执行信号分割

使用信号分类的时频方法派生特征。

函数

信号处理层

`cwtLayer`	Continuous wavelet transform (CWT) layer (自 R2022b 起)
`modwtLayer`	Maximal overlap discrete wavelet transform (MODWT) layer (自 R2022b 起)
`stftLayer`	Short-time Fourier transform layer (自 R2021b 起)
`istftLayer`	Inverse short-time Fourier transform layer (自 R2024a 起)

特征提取

`dlcwt`	Deep learning continuous wavelet transform (自 R2022b 起)
`dlmodwt`	Deep learning maximal overlap discrete wavelet transform and multiresolution analysis (自 R2022a 起)
`dlstft`	Deep learning short-time Fourier transform (自 R2021a 起)
`dlistft`	Deep learning inverse short-time Fourier transform (自 R2024a 起)
`cwtfilterbank`	Continuous wavelet transform filter bank
`findchangepts`	Find abrupt changes in signal
`findpeaks`	查找局部最大值
`modwt`	Maximal overlap discrete wavelet transform
`risetime`	Rise time of positive-going bilevel waveform transitions
`stft`	Short-time Fourier transform
`signalFrequencyFeatureExtractor`	Streamline signal frequency feature extraction (自 R2021b 起)
`signalTimeFeatureExtractor`	Streamline signal time feature extraction (自 R2021a 起)
`waveletScattering`	Wavelet time scattering

数据存储和数据管理

`edfheader`	Create header structure for EDF or EDF+ file (自 R2021a 起)
`edfinfo`	Get information about EDF/EDF+ file (自 R2020b 起)
`edfread`	Read data from EDF/EDF+ file (自 R2020b 起)
`edfwrite`	Create or modify EDF or EDF+ file (自 R2021a 起)
`paddata`	Pad data by adding elements (自 R2023b 起)
`resize`	Resize data by adding or removing elements (自 R2023b 起)
`trimdata`	Trim data by removing elements (自 R2023b 起)
`signalDatastore`	Datastore for collection of signals (自 R2020a 起)

模块

Wavelet Scattering

Model wavelet scattering network in Simulink (自 R2022b 起)

主题

Classify Arm Motions Using EMG Signals and Deep Learning (Signal Processing Toolbox)
Classify arm motions using labeled EMG signals and a long short-term memory network.
Detect Air Compressor Sounds in Simulink Using Wavelet Scattering (DSP System Toolbox)
Use the Wavelet Scattering block and a pretrained deep learning network to classify audio signals.
Detect Anomalies in ECG Data Using Wavelet Scattering and LSTM Autoencoder in Simulink (DSP System Toolbox)
Use wavelet scattering and deep learning network to detect anomalies in ECG signals.
Manage Data Sets for Machine Learning and Deep Learning Workflows (Signal Processing Toolbox)
Organize, access, and manage data sets for different AI applications.

精选示例

Machine and Deep Learning Classification Using Signal Feature Extraction Objects

Use signal feature extraction objects and AI-based classification to identify faulty bearing signals in mechanical systems.

打开实时脚本

Feature Selection Based on Deep Learning Interpretability for Signal Classification Applications

Use the locally interpretable model-agnostic explanation technique to interpret decision-making processes of a deep learning network.

打开实时脚本

Export Labeled Data from Signal Labeler for Deep Learning Classification

Label signals and export data using Signal Labeler to train a deep learning classifier.

打开实时脚本

Time-Frequency Convolutional Network for EEG Data Classification

Classify electroencephalographic (EEG) time series from persons with and without epilepsy.

打开实时脚本

Time-Frequency Feature Embedding with Deep Metric Learning

Construct wavelet-based feature embeddings to classify EEG signals from persons with and without epilepsy.

打开实时脚本

使用长短期记忆网络对 ECG 信号进行分类

使用深度学习和信号处理对心跳心电图数据进行分类。

打开实时脚本

使用小波分析和深度学习对时间序列分类

使用深度学习和连续小波变换对心跳心电图数据进行分类。

打开实时脚本

基于小波散射和深度学习的口述数字识别

使用机器学习和深度学习方法对语音数字进行分类。

打开实时脚本

Hand Gesture Classification Using Radar Signals and Deep Learning

Classify ultra-wideband impulse radar signal data using a MISO convolutional neural network.

打开实时脚本

分类

函数

信号处理层

特征提取

数据存储和数据管理

模块

主题

精选示例

Machine and Deep Learning Classification Using Signal Feature Extraction Objects

Feature Selection Based on Deep Learning Interpretability for Signal Classification Applications

Export Labeled Data from Signal Labeler for Deep Learning Classification

Time-Frequency Convolutional Network for EEG Data Classification

Time-Frequency Feature Embedding with Deep Metric Learning

使用长短期记忆网络对 ECG 信号进行分类

使用小波分析和深度学习对时间序列分类

基于小波散射和深度学习的口述数字识别

Hand Gesture Classification Using Radar Signals and Deep Learning

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