We study the limiting spectral measure of large symmetric random matrices of linear algebraic structure. For Hankel and Toeplitz matrices generated by i.i.d. random variables {Xk} of unit variance, and for symmetric Markov matrices generated by i.i.d. random variables {Xij}j>i of zero mean and unit variance, scaling the eigenvalues by √ n we prove the almost sure, weak convergence of the spectr...

In this paper we introduce a nonextensive quantum information theoretic measure which may be defined between any arbitrary number of density matrices, and we analyze its fundamental properties in the spectral graph-theoretic framework. Unlike other entropic measures, the proposed quantum divergence is symmetric, matrix-convex, theoretically upper-bounded, and has the advantage of being generali...

Nonlinear spectral mixture analysis (NSMA) is a widely used unmixing algorithm. It can fit the mixed spectra adequately, but collinearity effect among true and virtual endmembers will decrease the retrieval accuracies of endmember fractions. Use of linear spectral mixture analysis (LSMA) can effectively reduce the degree of collinearity in the NSMA. However, the inadequate modeling of mixed spe...

A novel multi-spectral focus measure that is based on algorithms for interest point detection, particularly on the FAST (Features from Accelerated Segment Test), Fast Hessian and Harris-Laplace detector, is described in this paper. The proposed measure methods are compared with commonly used focus measure techniques like energy of image gradient, sum-modified Laplacian, Tenenbaum’s algorithm or...

BACKGROUND The Datex-Ohmeda S/5 Entropy Module (Datex-Ohmeda Division, Instrumentarium Corp., Helsinki, Finland), using time-frequency balanced Spectral Entropy, is a novel tool for monitoring the hypnotic state during anesthesia. The Entropy Module produces two values, State Entropy (SE) and Response Entropy (RE), and in adults, it has been shown to measure reliably the hypnotic effects of var...

The asymptotic behavior for the spectral measure of a Kähler manifold has been studied by many authors in the context of Kähler quantization. It is well known that the spectral measure has an asymptotic expansion, while the coefficients of this expansion are not known even for very simple examples. In this thesis we study the spectral properties of Kähler manifolds assuming the existence of som...

satellite imagery was used as a rapid and spatially explicit method to delineate crop residue cover and to estimate the use and intensity of conservation tillage. the potential of multispectral high-spatial resolution of worldview-2 local data was evaluated using 11 satellite spectral indices and linear spectral unmixing analysis (lsua). experimental plots were examined; residue cover was measu...

The objective of this paper is to extend a promising objective speech distortion measurement method, the Bark Spectral Distance (BSD) measure, with the auditory concepts of forward and backward temporal masking to improve its measurement accuracy. The results of this investigation show that automatic BSD-based speech quality ratings may be made to correlate better with existing MOS ratings by r...

Due to catastrophic consequences of accidents by hazardous materials (hazmat) transportation, a risk-averse approach for routing is appropriate for risk mitigation. In this paper, we consider spectral risk measures, which are coherent and more general than existing approaches such as conditional value-at-risk. In spectral risk measures, one can define the spectrum function precisely to reflect ...

Process of identifying the end points of the acoustic units of the speech signal is called speech segmentation. Speech recognition systems can be designed using sub-word unit like phoneme. A Phoneme is the smallest unit of the language. It is context dependent and tedious to find the boundary. Automated phoneme segmentation is carried in researches using Short term Energy, Convex hull, Formant,...