Detecting critical regions in multidimensional data sets
نویسندگان
چکیده
We propose a new approach, based on the Conley index theory, for the detection and classification of critical regions in multidimensional data sets. The use of homology groups makes this method consistent and successful in all dimensions and allows to generalize visual classification techniques based solely on the notion of connectedness which may fail in higher dimensions.
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ورودعنوان ژورنال:
- Computers & Mathematics with Applications
دوره 61 شماره
صفحات -
تاریخ انتشار 2011