MCiSSA: Multivariate Circulant SSA under Matlab

Versión 1.2.1 (5,79 KB) por Juan Bógalo Román
Multivariate Circulant Singular Spectrum Analysis is a procedure for signal processing of multivariate time series
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Actualizado 22 ago 2023
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A set of MATLAB functions is presented for signals extraction by Multivariate Circulant Singular Spectrum Analysis (MCiSSA), a procedure proposed in Bógalo et al (2024). Multivariate Circulant SSA is a new variant of Multivariate SSA that allows to extract the signals associated to any frequency specied beforehand. The key for the self-identification of the frequencies is the use of block circulant matrices of second moments, instead of the usual variance-covariance matrix, that allows matching eigenvalues with frequencies. Additionally, MCiSSA performs a double diagonalization of that block circulant matrix that uncovers cross section relations per frequency.

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Juan Bógalo Román (2025). MCiSSA: Multivariate Circulant SSA under Matlab (https://github.com/jbogalo/MCiSSA/releases/tag/1.2.1), GitHub. Recuperado .

Bógalo, J., Poncela, P., & Senra, E. (2024). Understanding fluctuations through Multivariate Circulant Singular Spectrum Analysis. Expert Systems with Applications, 123827. https://doi.org/10.1016/j.eswa.2024.123827

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Se creó con R2021b
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1.2.1

Para consultar o notificar algún problema sobre este complemento de GitHub, visite el repositorio de GitHub.
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