Clasificación

Clasifique atributos de señal, lleve a cabo la segmentación de señales a través de la clasificación secuencia a secuencia

Derive características usando técnicas de tiempo-frecuencia para la clasificación de señales.

Funciones

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

`dlcwt`	Deep learning continuous wavelet transform (desde R2022b)
`dlmodwt`	Deep learning maximal overlap discrete wavelet transform and multiresolution analysis (desde R2022a)
`dlstft`	Deep learning short-time Fourier transform (desde R2021a)
`dlistft`	Deep learning inverse short-time Fourier transform (desde R2024a)
`cwtfilterbank`	Continuous wavelet transform filter bank
`findchangepts`	Find abrupt changes in signal
`findpeaks`	Encontrar los máximos locales
`modwt`	Maximal overlap discrete wavelet transform
`risetime`	Rise time of positive-going bilevel waveform transitions
`stft`	Transformada de Fourier de tiempo corto
`signalFrequencyFeatureExtractor`	Streamline signal frequency feature extraction (desde R2021b)
`signalTimeFeatureExtractor`	Streamline signal time feature extraction (desde R2021a)
`waveletScattering`	Wavelet time scattering

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

Model wavelet scattering network in Simulink (desde R2022b)

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.

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

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

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

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

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

Classify heartbeat electrocardiogram data using deep learning and signal processing.

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

Classify spoken digits using both machine learning and deep learning techniques.

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