PCA of waveforms and functional PCA: A primer for biomechanics

Variational Bayesian functional PCA

A Bayesian approach to analyze the modes of variation in a set of curves is suggested. It is based on a generative model thus allowing for noisy and sparse observations of curves. A Demmler-Reinsch(-type) basis is used to enforce smoothness of the latent (‘eigen’-)functions. Inference, including estimation, error assessment and model choice, particularly the choice of the number of eigenfunctio...

EM Algorithms for PCA and Sensible PCA

A Thermodynamic Study of the Interactions between Acetamide Derivatives and PCA-PEG-PCA Copolymers: ONIOM Calculations

To improve drug selectivity toward target cells, one interesting approach for drug delivery is to use polymer nanoparticles. A two-layered ONIOM Becke3- LYP: UFF calculation was carried out to study the structural and thermodynamic properties of the interaction between acetamide derivatives and the PCA-PEG-PCA copolymers. The Interaction enthalpies and the Gibbs free energies between acetamide ...

Consistent Functional Pca for Financial Time-series

Functional Principal Component Analysis (FPCA) provides a powerful and natural way to model functional financial data sets (such as collections of time-indexed futures and interest rate yield curves). However, FPCA assumes each sample curve is drawn from an independent and identical distribution. This assumption is axiomatically inconsistent with financial data; rather, samples are often interl...

Performance Evaluation of Face Recognition using PCA and N-PCA

Face recognition has become a valuable and routine forensic tool used by criminal investigators. It is an important area of computer vision research and has gained significant interest in recent years. Efforts in improving security, such as automatic surveillance and the use of biometrics in identification, are partly responsible for this increased interest. However, several challenges remain i...