도움말 센터 도움말 센터

이상 감지

신경망과 오토인코더를 사용하여 신호 이상 감지

웨이블릿을 기반으로 희소화된 시간-주파수 특징을 추출하여 이상을 감지합니다.

함수

오토인코더

deepSignalAnomalyDetector Create signal anomaly detector (R2023a 이후)

신호 처리 계층

`cwtLayer`	Continuous wavelet transform layer (R2022b 이후)
`icwtLayer`	Inverse continuous wavelet transform layer (R2024b 이후)
`modwtLayer`	Maximal overlap discrete wavelet transform layer (R2022b 이후)
`stftLayer`	Short-time Fourier transform layer (R2021b 이후)
`istftLayer`	Inverse short-time Fourier transform layer (R2024a 이후)

특징 추출

`dlcwt`	Deep learning continuous wavelet transform (R2022b 이후)
`dlicwt`	Deep learning inverse continuous 1-D wavelet transform (R2024b 이후)
`dlmodwt`	Deep learning maximal overlap discrete wavelet transform and multiresolution analysis (R2022a 이후)
`dlstft`	Deep learning short-time Fourier transform (R2021a 이후)
`dlistft`	Deep learning inverse short-time Fourier transform (R2024a 이후)
`cwtfilterbank`	Continuous wavelet transform filter bank
`findchangepts`	신호 내 급격한 변화 찾기
`findpeaks`	국소 최댓값 구하기
`modwt`	Maximal overlap discrete wavelet transform
`risetime`	Rise time of positive-going bilevel waveform transitions
`stft`	단시간 푸리에 변환
`signalFrequencyFeatureExtractor`	Streamline signal frequency feature extraction (R2021b 이후)
`signalTimeFeatureExtractor`	Streamline signal time feature extraction (R2021a 이후)
`signalTimeFrequencyFeatureExtractor`	Streamline signal time-frequency feature extraction (R2024a 이후)
`waveletScattering`	Wavelet time scattering

데이터저장소 및 데이터 관리

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

블록

Wavelet Scattering	Model wavelet scattering network in Simulink (R2022b 이후)
Deep Signal Anomaly Detector	Detect signal anomalies using deep learning network in Simulink (R2024a 이후)

도움말 항목

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.

추천 예제

Anomaly Detection Using Convolutional Autoencoder with Wavelet Scattering Sequences

Anomaly Detection Using Convolutional Autoencoder with Wavelet Scattering Sequences

Detect anomalies in acoustic data using wavelet scattering with the deepSignalAnomalyDetector object.

라이브 스크립트 열기

Anomaly Detection Using Autoencoder and Wavelets

Anomaly Detection Using Autoencoder and Wavelets

Use wavelet-extracted features and an autoencoder to detect arc signals in a DC system.

라이브 스크립트 열기

Crack Identification from Accelerometer Data

Crack Identification from Accelerometer Data

Use wavelet and deep learning techniques to detect transverse pavement cracks and localize their position.

라이브 스크립트 열기

Detect Anomalies Using Wavelet Scattering with Autoencoders

Detect Anomalies Using Wavelet Scattering with Autoencoders

Learn how to develop an alert system for predictive maintenance using wavelet scattering and deep learning.

라이브 스크립트 열기

Fault Detection Using Wavelet Scattering and Recurrent Deep Networks

Fault Detection Using Wavelet Scattering and Recurrent Deep Networks

Classify faults in acoustic recordings of air compressors using a wavelet scattering network paired with a recurrent neural network.

라이브 스크립트 열기

Detect Anomalies in Signals Using deepSignalAnomalyDetector

Detect Anomalies in Signals Using deepSignalAnomalyDetector

Use a learning-based tool to detect abnormal points or segments in time-series data.

라이브 스크립트 열기

Detect Anomalies in Machinery Using LSTM Autoencoder

Detect Anomalies in Machinery Using LSTM Autoencoder

Use a long short-term memory autoencoder to detect anomalies in data from an industrial machine.

라이브 스크립트 열기

Fault Detection and Localization in Three-Phase Power Transmission Using Deep Signal Anomaly Detector in Simulink

Fault Detection and Localization in Three-Phase Power Transmission Using Deep Signal Anomaly Detector in Simulink

Detect faults in three-phase power transmission using the Deep Signal Anomaly Detector block.

(DSP System Toolbox)