Measure signal-to-noise ratio (SNR), total harmonic distortion (THD), and signal-to-noise and distortion ratio (SINAD).Measure harmonic distortion. Compute the bandwidth and mean or median frequency for signals or power spectrum.Measure rise time, fall time, slew rate, overshoot, undershoot, settling time, pulse width, pulse period, and duty cycle. Locate signal peaks and determine their height, width, and distance to neighbors.Measure time-domain features such as peak-to-peak amplitudes and signal envelopes. Feature Extraction and Signal Measurements 3.1 Descriptive StatisticsĬompute common descriptive statistics like maxima, minima, standard deviations, and RMS levels.Find changepoints in signals and align signals using dynamic time warping. 使用 Signal Analyzer app对信号在时间、频率和时频域进行分析和可视化。Įxtract regions of interest from signals for further analysis.ĭenoise, smooth, and detrend signals to prepare them for further analysis.Remove outliers and spurious content from data.Įnhance signals, visualize them, and discover patterns.Change the sample rate of a signal or make the sample rate constant for irregularly sampled signals or signals with missing data. Use the Signal Analyzer app to analyze and visualize signals in the time, frequency, and time-frequency domains. Signal Exploration and Preprocessing 2.1 Exploring Signals
Use examples to get started with machine learning and deep learning for signals. Create different types of labels and sublabels. Use the Signal Labeler app to label signals with attributes, regions, and points of interest. Machine Learning and Deep Learning for Signals 1.1 Preprocessing and feature extraction
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