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Discover Dependencies from Data—A Review
IEEE Transactions on Knowledge and Data Engineering, 2012Traditionally dependencies are used in database design and data quality control. In knowledge discovery, dependencies represent knowledge discovered from the data of databases. Some of the discovered dependencies represent new knowledge in the application area, which is critical to the advance of the area, and some are used to verify existing knowledge.
Liu, Jixue +3 more
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A low complexity data-dependent beamformer
2008 IEEE Ultrasonics Symposium, 2008The classical problem of choosing apodization functions for a beamformer involves a trade-off between main lobe width and side lobe level, i.e., a trade-off between resolution and contrast. To avoid this trade-off, the application of adaptive beamforming, such as minimum variance beamforming, to medical ultrasound imaging has been suggested.
Johan-Fredrik, Synnevag +2 more
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Graphs of Data Flow Dependencies
IFAC Proceedings Volumes, 1979Data flow dependencies of a program are important for code-optimisation of compilers and for detecting errors in programs. The control flow of a program can be described by its control flow graph. The mutual dependencies of variables in a program can be represented by graphs, too.
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Data-Dependent Kernel Machines for Microarray Data Classification
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2007One important application of gene expression analysis is to classify tissue samples according to their gene expression levels. Gene expression data are typically characterized by high dimensionality and small sample size, which makes the classification task quite challenging.
Huilin, Xiong, Ya, Zhang, Xue-Wen, Chen
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2011
The world is not a static place—the conditions sensors describe vary over time. In some cases the variation is captured as a change in some state (e.g. light as day becomes night), in other cases the variation describes the reading (e.g. a motion detector) and in yet others the reading is encoded within a varying signal (e.g. sound). In this chapter we
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The world is not a static place—the conditions sensors describe vary over time. In some cases the variation is captured as a change in some state (e.g. light as day becomes night), in other cases the variation describes the reading (e.g. a motion detector) and in yet others the reading is encoded within a varying signal (e.g. sound). In this chapter we
openaire +1 more source