A Multiple Parameter Linear Scale-Space for one dimensional Signal Classification

• URL: http://arxiv.org/abs/2305.13350v1
• Date: Mon, 22 May 2023 17:14:45 GMT
• Title: A Multiple Parameter Linear Scale-Space for one dimensional Signal Classification
• Abstract summary: We construct a maximal set of kernels for a multi- parameter linear scale-space that allow us to construct trees for classification and recognition of one-dimensional continuous signals. A number of useful properties of the maximal set of kernels are derived. A new topologically invariant method of constructing trees is introduced.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this article we construct a maximal set of kernels for a multi-parameter linear scale-space that allow us to construct trees for classification and recognition of one-dimensional continuous signals similar the Gaussian linear scale-space approach. Fourier transform formulas are provided and used for quick and efficient computations. A number of useful properties of the maximal set of kernels are derived. We also strengthen and generalize some previous results on the classification of Gaussian kernels. Finally, a new topologically invariant method of constructing trees is introduced.

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