Abstract
The two more known paradigms of Neural Networks are usually considered as very different structures. In this paper both structures are studied from the point of view of a general formal hierarchical recursive framework for describing connectionist models. As a result of this study both paradigms are defined, using the same language, from a top level of abstraction, down to a level suitable for implementation. The final basic primitives of the descriptions are taken from a set of standard building blocks in computation.
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© 1997 Springer-Verlag Berlin Heidelberg
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Álvarez, J.R. (1997). Structural level comparison of two basic paradigms in neural computation. In: Mira, J., Moreno-Díaz, R., Cabestany, J. (eds) Biological and Artificial Computation: From Neuroscience to Technology. IWANN 1997. Lecture Notes in Computer Science, vol 1240. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0032549
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DOI: https://doi.org/10.1007/BFb0032549
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