On the granularity of summative kernels

In this paper, we propose granularity as a new index to characterize the nonspecificity of a summative kernel. This index is intended to reflect the behavior of a kernel in the usual signal processing applications. We show, in different experiments, that two kernels having the same granularity have very similar behavior. This granularity-based adaptation is compared to other adaptation methods. These experiments highlight the ability of the granularity index to measure the spreading and collecting properties of a summative kernel. Key words: summative, maxitive kernels, granularity, possibility, probability theory, signal processing, adaptation

• Type: Journal
• Year: 2008
• Where: FSS
• Authors: Kevin Loquin, Olivier Strauss
• Keywords: FSS 2008, Granularity, Summative Kernel, Usual Signal Processing