Conformal self-organization for continuity on a feature map
The self-organization model with a conformal-mapping adaptation is studied in this work. This model is designed to provide conformal transformation to meet the conformality requirement in biological morphology and geometrical surface mapping. This model spans the network field in the input space where topological conformality is preserved. The converged network provides not only the organized clustering features of the input but also a specific mapping representation. This facilitates the Kohonen's self-organization model in exploring the input in a continuous conformality sense. Simulations for morphing applications are described.
self-organization feature map conformal mapping schwarzchristoffel transformation simplex quantization morphological form facial modeling neural networks