Robust Tensor Analysis with Non-Greedy L1-Norm Maximization

The L1-norm based tensor analysis (TPCA-L1) is recently proposed for dimensionality reduction and feature extraction. However, a greedy strategy was utilized for solving the L1-norm maximization problem, which makes it prone to being stuck in local solutions. In this paper, we propose a robust TPCA with non-greedy L1-norm maximization (TPCA-L1 non-greedy), in which all projection directions are optimized simultaneously. Experiments on several face databases demonstrate the effectiveness of the proposed method

Polaronic transport induced by competing interfacial magnetic order in a La0.7_{0.7}Ca0.3_{0.3}MnO3_{3}/BiFeO3_{3} heterostructure

Using ultrafast optical spectroscopy, we show that polaronic behavior associated with interfacial antiferromagnetic order is likely the origin of tunable magnetotransport upon switching the ferroelectric polarity in a La$_{0.7}$Ca$_{0.3}$MnO$_{3}$/BiFeO$_{3}$ (LCMO/BFO) heterostructure. This is revealed through the difference in dynamic spectral weight transfer between LCMO and LCMO/BFO at low temperatures, which indicates that transport in LCMO/BFO is polaronic in nature. This polaronic feature in LCMO/BFO decreases in relatively high magnetic fields due to the increased spin alignment, while no discernible change is found in the LCMO film at low temperatures. These results thus shed new light on the intrinsic mechanisms governing magnetoelectric coupling in this heterostructure, potentially offering a new route to enhancing multiferroic functionality

Relaxed 2-D Principal Component Analysis by LpL_p Norm for Face Recognition

A relaxed two dimensional principal component analysis (R2DPCA) approach is proposed for face recognition. Different to the 2DPCA, 2DPCA-$L_1$ and G2DPCA, the R2DPCA utilizes the label information (if known) of training samples to calculate a relaxation vector and presents a weight to each subset of training data. A new relaxed scatter matrix is defined and the computed projection axes are able to increase the accuracy of face recognition. The optimal $L_p$-norms are selected in a reasonable range. Numerical experiments on practical face databased indicate that the R2DPCA has high generalization ability and can achieve a higher recognition rate than state-of-the-art methods.Comment: 19 pages, 11 figure

Facial expression recognition using histogram variances faces

In human's expression recognition, the representation of expression features is essential for the recognition accuracy. In this work we propose a novel approach for extracting expression dynamic features from facial expression videos. Rather than utilising statistical models e.g. Hidden Markov Model (HMM), our approach integrates expression dynamic features into a static image, the Histogram Variances Face (HVF), by fusing histogram variances among the frames in a video. The HVFs can be automatically obtained from videos with different frame rates and immune to illumination interference. In our experiments, for the videos picturing the same facial expression, e.g., surprise, happy and sadness etc., their corresponding HVFs are similar, even though the performers and frame rates are different. Therefore the static facial recognition approaches can be utilised for the dynamic expression recognition. We have applied this approach on the well-known Cohn-Kanade AU-Coded Facial Expression database then classified HVFs using PCA and Support Vector Machine (SVMs), and found the accuracy of HVFs classification is very encouraging. © 2009 IEEE

On the Convergence of Ritz Pairs and Refined Ritz Vectors for Quadratic Eigenvalue Problems

For a given subspace, the Rayleigh-Ritz method projects the large quadratic eigenvalue problem (QEP) onto it and produces a small sized dense QEP. Similar to the Rayleigh-Ritz method for the linear eigenvalue problem, the Rayleigh-Ritz method defines the Ritz values and the Ritz vectors of the QEP with respect to the projection subspace. We analyze the convergence of the method when the angle between the subspace and the desired eigenvector converges to zero. We prove that there is a Ritz value that converges to the desired eigenvalue unconditionally but the Ritz vector converges conditionally and may fail to converge. To remedy the drawback of possible non-convergence of the Ritz vector, we propose a refined Ritz vector that is mathematically different from the Ritz vector and is proved to converge unconditionally. We construct examples to illustrate our theory.Comment: 20 page

Coexistence of coupled magnetic phases in epitaxial TbMnO3 films revealed by ultrafast optical spectroscopy

Ultrafast optical pump-probe spectroscopy is used to reveal the coexistence of coupled antiferromagnetic/ferroelectric and ferromagnetic orders in multiferroic TbMnO3 films through their time domain signatures. Our observations are explained by a theoretical model describing the coupling between reservoirs with different magnetic properties. These results can guide researchers in creating new kinds of multiferroic materials that combine coupled ferromagnetic, antiferromagnetic and ferroelectric properties in one compound.Comment: Accepted by Appl. Phys. let