We study thermal Casimir and quantum nonretarded Lifshitz interactions between dielectrics in general geometries. We map the calculation of the classical partition function onto a determinant, which we discretize and evaluate with the help of Cholesky factorization. The quantum partition function is treated by path integral quantization of a set of interacting dipoles and reduces to a product o...

This paper presents a new kernel framework for hyperspectral images classification. In this paper, a new feature extraction algorithm based on wavelet kernel non-negative matrix factorization (WKNMF) for hyperspectral remote sensing images is proposed. By using the feature of multi-resolution analysis, the new method can improve the nonlinear mapping capability of kernel non-negative matrix fac...

Spectrogram factorization is a recent and promising alternative to sinusoidal or source/filter modeling for analysis/resynthesis systems aimed at musical creation. This paper presents a framework designed to perform a wide range of sound manipulations based on Non-negative Matrix Factorization (NMF), including a set of new techniques for creating artificial cross-components not present in the o...

Abstract—Nonnegative matrix factorization (NMF) is an emerging technique with a wide spectrum of potential applications in data analysis. Mathematically, NMF can be formulated as a minimization problem with nonnegative constraints. This problem is currently attracting much attention from researchers for theoretical reasons and for potential applications. Currently, the most popular approach to ...

Spectral envelope is one of the most important features that characterize the timbre of an instrument sound. However, it is difficult to use spectral information in the framework of conventional spectrogram decomposition methods. We overcome this problem by suggesting a simple way to provide a constraint on the spectral envelope calculated by linear prediction. In the first part of this study, ...

This paper presents a novel mid-level representation for action recognition, named spatio-temporal aware non-negative component representation (STANNCR). The proposed STANNCR is based on action component and incorporates the spatial-temporal information. We first introduce a spatial-temporal distribution vector (STDV) to model the distributions of local feature locations in a compact and discri...

A model for localized key finding from audio is proposed. Besides being able to estimate the key in which a piece starts, the model can also identify points of modulation and label multiple sections with their key names throughout a single piece. The front-end employs an adaptive tuning stage prior to spectral analysis and calculation of chroma features. The segmentation stage uses groups of co...