Introduces a sampling pseudospectrum P(λ) and estimator ˆP(λ) obtained by reprocessing finite data to statistically test the location of true eigenvalues versus sampling artifacts in data-driven matrices.
Freedman’s inequality for matrix martingales.Electronic Communications in Prob- ability, 16:262–270, 2011
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Sampling pseudospectrum for data-driven matrices
Introduces a sampling pseudospectrum P(λ) and estimator ˆP(λ) obtained by reprocessing finite data to statistically test the location of true eigenvalues versus sampling artifacts in data-driven matrices.