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 Multilinear Subspace Learning: Dimensionality Reduction of Multidimensional Data
Due to advances in sensor, storage, and networking technologies, data is being generated on a daily basis at an ever-increasing pace in a wide range of applications, including cloud computing, mobile Internet, and medical imaging. This large multidimensional data requires more efficient dimensionality reduction schemes than the traditional... |  |  Digital Control
Digital control systems are becoming increasingly prevalent and important within industry. In recent years significant progress has been made in their analysis and design – particularly within the areas of microprocessors and digital signal processors. The traditional approach to teaching digital control assumes an understanding of... |  |  Sparse Image and Signal Processing: Wavelets, Curvelets, Morphological Diversity
This book presents the state of the art in sparse and multiscale image and signal processing, covering linear multiscale transforms, such as wavelet, ridgelet, or curvelet transforms, and non-linear multiscale transforms based on the median and mathematical morphology operators. Recent concepts of sparsity and morphological diversity are... |
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