Signal Processing Toolbox
Signal Processing Toolbox™ provides functions and apps to manage, analyze, preprocess, and extract features from uniformly and nonuniformly sampled signals. The toolbox includes tools for filter design and analysis, resampling, smoothing, detrending, and power spectrum estimation. You can use the Signal Analyzer app for visualizing and processing signals simultaneously in time, frequency, and time-frequency domains. With the Filter Designer app you can design and analyze FIR and IIR digital filters. Both apps generate MATLAB® scripts to reproduce or automate your work.
Using toolbox functions, you can prepare signal datasets for AI model training by engineering features that reduce dimensionality and improve the quality of signals. You can access and process collections of files and large datasets using signal datastores. With the Signal Labeler app, you can annotate signal attributes, regions, and points of interest to create labeled signal sets. The toolbox supports GPU acceleration in addition to C/C++ and CUDA® code generation for desktop prototyping and embedded system deployment.
Learn the basics of Signal Processing Toolbox
Visualize, preprocess, and explore signals using Signal Analyzer app
Create, resample, smooth, denoise, and detrend signals
Peaks, signal statistics, pulse and transition metrics, power, bandwidth, distortion
Cross-correlation, autocorrelation, Fourier, DCT, Hilbert, Goertzel, parametric modeling, linear predictive coding
FIR and IIR, single-rate and multirate filter design, analysis, and implementation
Power spectrum, coherence, windows
Spectrogram, synchrosqueezing, reassignment, Wigner-Ville, time-frequency marginals, data-adaptive methods
Order analysis, time-synchronous averaging, envelope spectra, modal analysis, rainflow counting
Signal labeling, feature engineering, dataset generation
Generate portable C/C++/MEX functions and use GPUs to deploy or accelerate processing