Inferring shape evolution

Dynamic shapes represent an important issue in several scientific and technological contexts. The current article presents a model-based mathematic-computational approach for inferring the processes of neural evolution, including analytical mappings, convolution models and normal wavefront propagation, illustrated with respect to stationary and non-stationary evolutions along time and space. 2002 Elsevier Science B.V. All rights reserved.

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