MATHEMATICAL MODELING FOR DATA ANALYSIS

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Pattern recognition methods aim at classifying elements of interest based on experimental measures extracted from them. It plays a central role in most data analysis problems involved in the USP-e-Science center. Pattern recognition applications may be found in a many different fields such as in image analysis, signal processing and computational biology. Among the modern challenges faced by the researchers in the field, it is worth mentioning 3 research topics of particular interest for the USP-e-Science: i) problems where the different elements should be structurally described as networks with connections linking those elements; ii) dynamic problems where the information may evolve along some independent variable (e.g. time in context of the video sequences); iii) problems that present both structural and dynamic aspects, i.e. a network of elements presenting a dynamic evolution along some independent variable.