There is much more information in a stochastic non-Gaussian or deterministic signal than is conveyed by its autocorrelation and power
spectrum. Higher-order spectra which are defined in terms of the higher-order moments or cumulants of a signal, contain this additional information. The Higher-Order Spectral Analysis (HOSA) Toolbox provides comprehensive higher-order spectral analysis capabilities for signal processing applications. The toolbox is an excellent resource for the advanced researcher and the practicing engineer, as well as the novice
student who wants to learn about concepts and algorithms in statistical signal processing.
The HOSA Toolbox is a collection of M-files that implement a variety of advanced signal processing algorithms for the estimation of cross- and auto-cumulants (including correlations), spectra and olyspectra,bispectrum, and bicoherence, and omputation of time-frequency
distributions. Based on these, algorithms for parametric and non-parametric blind system identification, time-delay estimation, harmonic retrieval, phase-coupling, direction of arrival estimation, parameter estimation of Volterra (non-linear) models, and adaptive linear prediction are implemented. Also included are algorithms for testing of Gaussianity and Linearity of a time series. A full tutorial and demo set are included in the toolbox.
Ananthram Swami (2022). HOSA - Higher Order Spectral Analysis Toolbox (https://www.mathworks.com/matlabcentral/fileexchange/3013-hosa-higher-order-spectral-analysis-toolbox), MATLAB Central File Exchange. Retrieved .
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