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| | Numerical Methods in Engineering with MATLABThis book is targeted primarily toward engineers and engineering students of advanced standing (sophomores, seniors and graduate students). Familiarity with a computer language is required; knowledge of basic engineering subjects is useful, but not essential.
The text attempts to place emphasis on numerical methods, not... | | Essential MATLAB for Scientists and EngineersBased on a teach-yourself approach, the fundamentals of MATLAB are illustrated throughout with many examples from a number of different scientific and engineering areas, such as simulation, population modelling, and numerical methods, as well as from business and everyday life. Some of the examples draw on first-year university level maths, but... |
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Biosignal and Biomedical Image ProcessingRelying heavily on MATLAB® problems and examples, as well as simulated data, this text/reference surveys a vast array of signal and image processing tools for biomedical applications, providing a working knowledge of the technologies addressed while showcasing valuable implementation procedures, common pitfalls, and essential application... | | 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... | | Hyperspectral Data Processing: Algorithm Design and Analysis
Hyperspectral Data Processing: Algorithm Design and Analysis is a culmination of the research conducted in the Remote Sensing Signal and Image Processing Laboratory (RSSIPL) at the University of Maryland, Baltimore County. Specifically, it treats hyperspectral image processing and hyperspectral signal processing as separate subjects in... |
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