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Two-component Structure in the Entanglement Spectrum of Highly Excited States
Two-component Structure Entanglement Spectrum Highly Excited States
2016/1/22
We study the entanglement spectrum of highly excited eigenstates of two known models that exhibit a many-body localization transition, namely the one-dimensional random-field Heisenberg model and the ...
In this paper, we study the problem of recovering a low-rank matrix (the principal components) from a highdimensional data matrix despite both small entry-wise noise and gross sparse errors. Recently,...
Image Quality Assessment Using Spatial Frequency Component
Image Quality Assessment Spatial Frequency Component
2010/12/20
Image quality assessment (IQA) is a crucial technique in perceptual image/video coding, because it is not only a ruler for performance evaluation of coding algorithms but also a metric for ratio-disto...
Modeling Sound Changes in Mandarin Spontaneous Speech Using Deleted In-terpolation of Mixture Component Weights
Sound Changes Deleted Int erpolation Hand-labeled
2013/6/27
The high error rate of recognition accuracy in spontaneous speech is due in part to the poor modeling of pronun-ciations variations. An analysis of the acousticdata reveals that the variati ons includ...
Component-based Cascade Linear Discriminant Analysis for Face Recognition
Component-based Cascade Linear Discriminant Analysis Face Recognition
2010/12/15
This paper presents a novel face recognition method based on cascade Linear Discriminant Analysis (LDA) of the component-based face representation. In the proposed method, a face image is represented ...