Abstract
The status of approaches to the solution of generalized inverse problems is reviewed in a broad context, and an apparent divergence in viewpoint is discussed. Both those of the mathematical school of deductive inversion, and their colleagues who concentrate on the extraction of solid information from limited data, often stand in ignorance of the work of one another while addressing different aspects of the same general problem. It is argued that these differing views are not in opposition but are actually complementary, and that each approach may well benefit from the ideas of the other. In particular, analysis of incomplete data must logically take place before, and provide input to, the application of any powerful mathematical machinery employed for, say, reconstructing an object.
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Grandy, W.T. (1985). Incomplete Information and Generalized Inverse Problems. In: Smith, C.R., Grandy, W.T. (eds) Maximum-Entropy and Bayesian Methods in Inverse Problems. Fundamental Theories of Physics, vol 14. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-2221-6_1
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