Signal Processing Toolbox™ provides apps and functions that let you analyze, visualize, and compare multiple signals and detect and extract features or interesting events. For example, with the Signal Analyzer app, you can:
Signal Processing Toolbox provides functions that let you detect outliers, smooth and work with irregularly sampled signals, and prepare them for further analysis. For example, you can:
Signal Processing Toolbox provides functions that let you explore and extract patterns in signals. Specifically, you can:
Use the functions and apps within Signal Processing Toolbox to design, analyze, and implement a variety of digital FIR and IIR filters, such as lowpass, highpass, and bandstop. With these functions and apps, you can:
Signal Processing Toolbox provides functions for analog filter design and analysis. Supported analog filter types include Butterworth, Chebyshev, Bessel, and elliptic. The toolbox also contains discretization functions, such as the impulse invariance and bilinear transformation methods for analog-to-digital filter conversion.
Characterize the frequency content of a signal using the family of spectral analysis functions and apps within Signal Processing Toolbox. FFT-based nonparametric methods, such as Welch's method or the periodogram, make no assumptions about the input data and can be used with any kind of signal. Parametric and subspace methods, such as Burg's, Yule-Walker, and MUSIC, incorporate prior knowledge of the signal and can yield more accurate spectral estimates. With these functions and apps, you can:
Signal Processing Toolbox provides functions that let you study and characterize vibrations in mechanical systems. Specifically, you can: