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The performance of a maximum likelihood (ML) based modulation classifier is highly sensitive to whether the model matches the real situation. In this paper, the quadrature amplitude modulation (QAM) signals are concerned and a ML modulation classifier which is robust to frequence offset, phase jitter, amplitude fluctuation and time delay is proposed. A new model is proposed to represent constellation...
In this paper we develop three manifold regression approaches for estimating quantitative metrics characterizing subsurface zones contaminated by Dense Non-Aqueous Phase Liquids (DNAPLs) based on sparse down-gradient concentration data. We are particularly interested in estimating source zone characteristics related to the distribution of contaminant mass in highly saturated pool regions as well as...
We present a face recognition method based on sparse representation for recognizing 3D face meshes under expressions using low-level geometric features. First, to enable the application of the sparse representation framework, we develop a uniform remeshing scheme to establish a consistent sampling pattern across 3D faces. To handle facial expressions, we design a feature pooling and ranking scheme...
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