Spectral Deconvolution through Bayesian LARS-OLS
Spectral Deconvolution through Bayesian LARS-OLS is a scholarly work, published in 2018 in ''Journal of the Physical Society of Japan''. The main subjects of the publication include independent component analysis, deconvolution, computer science, Spectral density estimation, Wiener deconvolution, statistics, fault detection and isolation, blind deconvolution, chemometrics, mathematics, algorithm, and Bayesian probability. The authors propose two spectral deconvolution methods, namely Bayesian LARS-OLS spectral deconvolution and LARS-OLS spectral deconvolution, both of which divide the procedure of spectral deconvolution into two steps: basis search and regression.