background: the objective of this study is to establish raman signatures from pure cultures of different candida species using raman spectroscopy (rs) and use these signatures for rapid identification of unknown candida species. methods: pure cultures of five candida species were evaluated using rs to build a limited signature library. ‘raman processing’ (rp) software was used for principal com...

The principle of dimensionality reduction with PCA is the representation of the dataset ‘X’in terms of eigenvectors ei ∈ RN  of its covariance matrix. The eigenvectors oriented in the direction with the maximum variance of X in RN carry the most      relevant information of X. These eigenvectors are called principal components [8]. Ass...

In this paper, we introduce a computational framework for recovering high-resolution approximation of an unknown function from its low-resolution indirect measurements as well training observations by merging the frameworks generalized sampling and functional principal component analysis. particular, increase signal resolution via data-driven approach, which models interest realization random f...