Algorithm-Eigenvalue Estimation of Hyperspectral Wishart Covariance Matrices from a Limited Number of Samples | Zendy

Avishai BenDavid | Zendy; Charles E. Davidson | Zendy

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Algorithm-Eigenvalue Estimation of Hyperspectral Wishart Covariance Matrices from a Limited Number of Samples

Author(s) -

Avishai BenDavid,

Charles E. Davidson

Publication year - 2015

Language(s) - English

Resource type - Reports

DOI - 10.21236/ada619977

Subject(s) - wishart distribution , hyperspectral imaging , covariance , estimation of covariance matrices , mathematics , eigenvalues and eigenvectors , estimation , covariance matrix , statistics , computer science , artificial intelligence , multivariate statistics , physics , engineering , quantum mechanics , systems engineering

: This MATLAB function is an algorithm designed to improve the eigenvalue estimates of Wishart-distributed covariance matrices and to recompute a revised covariance matrix from the eigenvalues. The MATLAB function is an implementation of the procedure developed and published by Avishai Ben-David and Charles E. Davidson (Eigenvalue Estimation of Hyperspectral Wishart Covariance Matrices from Limited Number of Samples. IEEE Trans. Geosci. Remote Sens. 2012, 50(11), pp 4384 4396).

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