Abstract

This paper introduces the concept of <i>eigenvalue manipulating transformation</i> (EMT) of a data matrix for noise suppression in two-dimensional (2D) correlation spectroscopy. The FT-IR spectra of a polystyrene/methyl ethyl ketone/toluene solution mixture during the solvent evaporation process, to which were added a substantial amount of artificial noise, have been analyzed. By uniformly raising the power of a set of eigenvalues, the major eigenvalues become more prominent. As a consequence, minor eigenvectors representing the noise component are no longer strongly represented in the reconstructed data. This EMT operation is similar to the simple truncation of noise-dominated minor factors practiced in standard principal component analysis (PCA), as demonstrated in our preceding paper on PCA-2D correlation spectroscopy. The effect of this new EMT scheme is more gradual, with attractive flexibility to continuously fine-tune the balance between the desired noise reduction effect and the retention of pertinent spectral information.

General noise suppression scheme with reference detection in heterodyne nonlinear spectroscopy

Yuan Feng, Ilya Vinogradov, and Nien-Hui Ge
Opt. Express 25(21) 26262-26279 (2017)

Eigenvectors of optimal color spectra

Mika Flinkman, Hannu Laamanen, Jukka Tuomela, Pasi Vahimaa, and Markku Hauta-Kasari
J. Opt. Soc. Am. A 30(9) 1806-1813 (2013)

Resonance lineshapes in two-dimensional Fourier transform spectroscopy

Mark E. Siemens, Galan Moody, Hebin Li, Alan D. Bristow, and Steven T. Cundiff
Opt. Express 18(17) 17699-17708 (2010)

Reflection optical two-dimensional Fourier-transform spectroscopy

Hebin Li, Galan Moody, and Steven T. Cundiff
Opt. Express 21(2) 1687-1692 (2013)

Improving the signal-to-noise ratio of atomic transitions in LIBS using two-dimensional correlation analysis

Linga Murthy Narlagiri and Venugopal Rao Soma
OSA Continuum 4(9) 2423-2441 (2021)