A unifying maximum-likelihood view of cumulant and polyspectral measures for non-Gaussian signal classification and estimation

DOI10.1109/18.119695zbMath0742.62091OpenAlexW2152693249MaRDI QIDQ3990774

Michail K. Tsatsanis, Georgios B. Giannakis

Publication date: 28 June 1992

Published in: IEEE Transactions on Information Theory (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1109/18.119695

zbMATH Keywords

pattern recognitioncumulantsARMA modelsidentifiabilitypolyspectraorder determinationmodel validation testsARMA parameter estimatorsasymptotically optimum maximum-likelihood classifiersnon-Gaussian signals observed in additive Gaussian noise of unknown covariance

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Inference from stochastic processes and spectral analysis (62M15) Signal detection and filtering (aspects of stochastic processes) (60G35) Survival analysis and censored data (62N99) Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

Related Items (3)

Consistent identification of stochastic linear systems with noisy input- output data ⋮ Blind channel estimation and deconvolution in colored noise using higher-order cumulants ⋮ Identifiability of general ARMA processes using linear cumulant-based estimators

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