A controversial issue in the research of mathematics of intelligence has been that of the roles of a priori knowledge versus adaptive learning. After discussing mathematical difficulties of combining a priority with adaptivity encountered in the past, we introduce a concept of a model-based neural network, whose adaptive learning is based on a priori models. Applications to target detection in SAR images are discussed. We briefly overview the SAR principles, derive relatively simple physics-based models of SAR signals, and describe model-based neural networks that utilize these models. A number of real-world application examples are presented.
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Perlovsky et al. (1997) studied this question.
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