Neural-network-based adaptive sampling of three-dimensional-object surface elastic properties

The paper discusses an adaptive-sampling technique for dimensionality reduction of the set of probing points in the measurement of nonuniform elastic properties of three-dimensional (3-D) objects. Two self-organizing neural-network architectures are compared for this purpose: the neural-gas network and the Kohonen self-organizing map (SOM).