Information-based objective functions for active data selection
Neural Computation
Active learning for adaptive mobile sensing networks
Proceedings of the 5th international conference on Information processing in sensor networks
Multiscale approximation with hierarchical radial basis functions networks
IEEE Transactions on Neural Networks
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This work focuses on the observation of environmental phenomena that occur as spatial distributions in two and three dimensions, using sensor-enabled mobile vehicles(ground,air or undersea). Algorithms to guide an adaptive exploration of a given region through systematic choice of sampling locations under the constraints imposed by vehicles are presented. Variation sensitive multiresolution sample distributions are achieved through an iterative variation sensitive estimation of the unknown process.