However, a number of new applications have emerged where the set-up can hardly be modeled naturally by one single frame system. They generally share a common property that requires distributed processing such as sensor networks. Furthermore, we are often overwhelmed by a deluge of data assigned to one single frame system, which becomes simply too large to be handled numerically. In these cases it would be highly beneficial to split a large frame system into a set of (overlapping) much smaller systems, and being able to process effectively locally within each sub-system. Interestingly, also our brain stores and processes information by using distributed processing techniques.
A distributed frame theory relating to a set of local frame systems is clearly in demand.
This led to the development of a suitable theory based on
fusion frames, which provides exactly
the framework not only to model these applications but also to provide efficient algorithms
with sufficient robustness. It can be shown that fusion frames contain conventional frames as a very special
case, thereby going beyond frame theory...
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