| Popis: |
Understanding and organizing data, in particular understanding the key modes of variation in the data, is a first step toward exploiting and evaluating sensor phenomenology. Spectral theory and manifold learning methods have been recently shown to offer sever powerful tools for many parts of the exploitation problem. We will describe the method of diffusion maps and give some examples with radar (backhoe data dome) data. The so-called diffusion coordinates are kernel based dimensionality reduction techniques that can, for example, organize random data and yield explicit insight into the type and relative importance of the data variation. We will provide sufficient background for others to adopt these tools and apply them to other aspects of exploitation and evaluation. |
