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By combining Kohonen learning and Grossberg learning a new type of mapping neural network is obtained. This counterpropagation network (CPN) functions as a statistically optimal self-programming lookup table. The paper begins with some introductory comments, followed by the definition of the CPN. Then a closedform formula for the error of the network is developed. The paper concludes with a discussion of CPN variants and comments about CPN convergence and performance. References and a neurocomputing bibliography with a combined total of eighty entries are provided.
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Robert Hecht-Nielsen (Tue,) studied this question.
synapsesocial.com/papers/6a15a122814bf8ec9a4edc53 — DOI: https://doi.org/10.1364/ao.26.004979
Robert Hecht-Nielsen
University of California, San Diego
Applied Optics
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