Abstract
Neural networks are meant to interact with the natural environment, and information about the latter is usually gathered through very noisy but redundant sensory signals. On the other hand, in the control of effectors or actuators (muscles, motors, etc.) one often has to coordinate many mutually dependent and redundant signals. In both cases, neural networks can be used to implement a great number of implicitly or otherwise poorly defined transformations between the variables.
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© 1997 Springer-Verlag Berlin Heidelberg
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Kohonen, T. (1997). Applications. In: Self-Organizing Maps. Springer Series in Information Sciences, vol 30. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-97966-8_7
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DOI: https://doi.org/10.1007/978-3-642-97966-8_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-62017-4
Online ISBN: 978-3-642-97966-8
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