Spectral Estimation
Analyze the spectral content of uniformly or nonuniformly sampled signals using
periodogram, pwelch, or plomb.
Sharpen periodogram estimates using reassignment. Determine frequency-domain coherence
between signals. Estimate transfer functions based on input and output measurements. Study
MIMO systems in the frequency domain.
Apps
| Signal Analyzer | Visualize and compare multiple signals and spectra |
Functions
Topics
Learn about the periodogram, modified periodogram, Welch, and multitaper methods of nonparametric spectral estimation.
Detect a Distorted Signal in Noise
Use frequency analysis to characterize a signal embedded in noise.
Detect Periodicity in a Signal with Missing Samples
Use the Lomb-Scargle periodogram to study the periodicity of an irregularly sampled signal.
Estimate the width of the frequency band that contains most of the power of a signal. For distorted signals, determine the power stored in the fundamental and the harmonics.
Amplitude Estimation and Zero Padding
Obtain an accurate estimate of the amplitude of a sinusoidal signal using zero padding.
Bias and Variability in the Periodogram
Reduce bias and variability in the periodogram using windows and averaging.
Compare the Frequency Content of Two Signals
Identify similarity between signals in the frequency domain.
Significance Testing for Periodic Component
Assess the significance of a sinusoidal component in white noise using Fisher's g-statistic.
Find Periodicity in a Categorical Time Series
Perform spectral analysis of data whose values are not inherently numerical.
Cross Spectrum and Magnitude-Squared Coherence
Obtain the phase lag between sinusoidal components and identify frequency-domain correlation in a time series.
Nonparametric Spectrum Object to Function Replacement
Replace calls to nonparametric psd and msspectrum objects
with function calls.
